{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "7ca8ea37-9fa0-40d7-b651-59639b599085",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: jieba in c:\\anaconda\\lib\\site-packages (0.42.1)\n"
     ]
    }
   ],
   "source": [
    "!pip install jieba"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "03fc74c6-a15d-4af6-bd05-204ee846a7f8",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>content</th>\n",
       "      <th>creationTime</th>\n",
       "      <th>nickname</th>\n",
       "      <th>referenceName</th>\n",
       "      <th>content_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>东西收到这么久，都忘了去好评，美的大品牌，值得信赖，东西整体来看，个人感觉还不错，没有出现什...</td>\n",
       "      <td>2017-04-17 13:01:54</td>\n",
       "      <td>鑫***辰</td>\n",
       "      <td>美的（Midea）60升预约洗浴 无线遥控 电热水器 F60-15WB5(Y)</td>\n",
       "      <td>pos</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>安装师傅很给力，热水器也好用，感谢美的。</td>\n",
       "      <td>2017-04-17 10:45:33</td>\n",
       "      <td>切***药</td>\n",
       "      <td>美的（Midea）60升预约洗浴 无线遥控 电热水器 F60-15WB5(Y)</td>\n",
       "      <td>pos</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>还没安装，基本满意</td>\n",
       "      <td>2017-04-17 10:58:33</td>\n",
       "      <td>j***x</td>\n",
       "      <td>美的（Midea）60升预约洗浴 无线遥控 电热水器 F60-15WB5(Y)</td>\n",
       "      <td>pos</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>电热水器收到了，京东自营商品就是好，发货速度快，品质有保障，安装效果好，宝贝非常喜欢，冬天可...</td>\n",
       "      <td>2017-10-18 20:22:33</td>\n",
       "      <td>j***2</td>\n",
       "      <td>美的（Midea）60升预约洗浴 无线遥控 电热水器 F60-15WB5(Y)</td>\n",
       "      <td>pos</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>用了几次才来评价，对产品非常满意，加热快保温时间长，售后服务特别好，主动打电话询问送货情况帮...</td>\n",
       "      <td>2017-04-17 09:19:16</td>\n",
       "      <td>j***6</td>\n",
       "      <td>美的（Midea）60升预约洗浴 无线遥控 电热水器 F60-15WB5(Y)</td>\n",
       "      <td>pos</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995</th>\n",
       "      <td>差评，差的一塌糊涂，千万别买，上当了，</td>\n",
       "      <td>2016-11-25 14:57:52</td>\n",
       "      <td>沫沫19900404</td>\n",
       "      <td>美的（Midea）60升预约洗浴 无线遥控 电热水器 F60-15WB5(Y)</td>\n",
       "      <td>neg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>热水器还没有安装，就搞一肚子气，安装人员今天推明天，明天推后天，售后安装服务太差，给差评，目...</td>\n",
       "      <td>2016-11-25 13:39:28</td>\n",
       "      <td>j***l</td>\n",
       "      <td>美的（Midea）60升预约洗浴 无线遥控 电热水器 F60-15WB5(Y)</td>\n",
       "      <td>neg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>好不容易网购一下还漏电</td>\n",
       "      <td>2016-11-25 13:38:49</td>\n",
       "      <td>K***T</td>\n",
       "      <td>美的（Midea）60升预约洗浴 无线遥控 电热水器 F60-15WB5(Y)</td>\n",
       "      <td>neg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>东西送的挺快，后期报装2天还没人联系我，售后太差</td>\n",
       "      <td>2016-11-25 10:19:20</td>\n",
       "      <td>j***p</td>\n",
       "      <td>美的（Midea）60升预约洗浴 无线遥控 电热水器 F60-15WB5(Y)</td>\n",
       "      <td>neg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>买了两个，送到一个，还有一个至今未送到。</td>\n",
       "      <td>2016-11-25 10:17:45</td>\n",
       "      <td>s***8</td>\n",
       "      <td>美的（Midea）60升预约洗浴 无线遥控 电热水器 F60-15WB5(Y)</td>\n",
       "      <td>neg</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2000 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                content         creationTime  \\\n",
       "0     东西收到这么久，都忘了去好评，美的大品牌，值得信赖，东西整体来看，个人感觉还不错，没有出现什...  2017-04-17 13:01:54   \n",
       "1                                  安装师傅很给力，热水器也好用，感谢美的。  2017-04-17 10:45:33   \n",
       "2                                             还没安装，基本满意  2017-04-17 10:58:33   \n",
       "3     电热水器收到了，京东自营商品就是好，发货速度快，品质有保障，安装效果好，宝贝非常喜欢，冬天可...  2017-10-18 20:22:33   \n",
       "4     用了几次才来评价，对产品非常满意，加热快保温时间长，售后服务特别好，主动打电话询问送货情况帮...  2017-04-17 09:19:16   \n",
       "...                                                 ...                  ...   \n",
       "1995                                差评，差的一塌糊涂，千万别买，上当了，  2016-11-25 14:57:52   \n",
       "1996  热水器还没有安装，就搞一肚子气，安装人员今天推明天，明天推后天，售后安装服务太差，给差评，目...  2016-11-25 13:39:28   \n",
       "1997                                        好不容易网购一下还漏电  2016-11-25 13:38:49   \n",
       "1998                           东西送的挺快，后期报装2天还没人联系我，售后太差  2016-11-25 10:19:20   \n",
       "1999                               买了两个，送到一个，还有一个至今未送到。  2016-11-25 10:17:45   \n",
       "\n",
       "        nickname                            referenceName content_type  \n",
       "0          鑫***辰  美的（Midea）60升预约洗浴 无线遥控 电热水器 F60-15WB5(Y)          pos  \n",
       "1          切***药  美的（Midea）60升预约洗浴 无线遥控 电热水器 F60-15WB5(Y)          pos  \n",
       "2          j***x  美的（Midea）60升预约洗浴 无线遥控 电热水器 F60-15WB5(Y)          pos  \n",
       "3          j***2  美的（Midea）60升预约洗浴 无线遥控 电热水器 F60-15WB5(Y)          pos  \n",
       "4          j***6  美的（Midea）60升预约洗浴 无线遥控 电热水器 F60-15WB5(Y)          pos  \n",
       "...          ...                                      ...          ...  \n",
       "1995  沫沫19900404  美的（Midea）60升预约洗浴 无线遥控 电热水器 F60-15WB5(Y)          neg  \n",
       "1996       j***l  美的（Midea）60升预约洗浴 无线遥控 电热水器 F60-15WB5(Y)          neg  \n",
       "1997       K***T  美的（Midea）60升预约洗浴 无线遥控 电热水器 F60-15WB5(Y)          neg  \n",
       "1998       j***p  美的（Midea）60升预约洗浴 无线遥控 电热水器 F60-15WB5(Y)          neg  \n",
       "1999       s***8  美的（Midea）60升预约洗浴 无线遥控 电热水器 F60-15WB5(Y)          neg  \n",
       "\n",
       "[2000 rows x 5 columns]"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import re\n",
    "import jieba.posseg as psg\n",
    "import warnings\n",
    "reviews = pd.read_csv(\"D:/Users/19202/Desktop/reviews.csv\")\n",
    "reviews"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "16f1630e-762a-40e0-8720-da6dbe51b888",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 删除数据记录中所有列值相同的记录\n",
    "reviews = reviews[['content','content_type']].drop_duplicates()\n",
    "content = reviews['content']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "3f41d6d5-85dc-484e-a0a1-30829e3a3282",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>content</th>\n",
       "      <th>content_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>东西收到这么久，都忘了去好评，美的大品牌，值得信赖，东西整体来看，个人感觉还不错，没有出现什...</td>\n",
       "      <td>pos</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>安装师傅很给力，热水器也好用，感谢美的。</td>\n",
       "      <td>pos</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>还没安装，基本满意</td>\n",
       "      <td>pos</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>电热水器收到了，京东自营商品就是好，发货速度快，品质有保障，安装效果好，宝贝非常喜欢，冬天可...</td>\n",
       "      <td>pos</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>用了几次才来评价，对产品非常满意，加热快保温时间长，售后服务特别好，主动打电话询问送货情况帮...</td>\n",
       "      <td>pos</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995</th>\n",
       "      <td>差评，差的一塌糊涂，千万别买，上当了，</td>\n",
       "      <td>neg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>热水器还没有安装，就搞一肚子气，安装人员今天推明天，明天推后天，售后安装服务太差，给差评，目...</td>\n",
       "      <td>neg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>好不容易网购一下还漏电</td>\n",
       "      <td>neg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>东西送的挺快，后期报装2天还没人联系我，售后太差</td>\n",
       "      <td>neg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>买了两个，送到一个，还有一个至今未送到。</td>\n",
       "      <td>neg</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1974 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                content content_type\n",
       "0     东西收到这么久，都忘了去好评，美的大品牌，值得信赖，东西整体来看，个人感觉还不错，没有出现什...          pos\n",
       "1                                  安装师傅很给力，热水器也好用，感谢美的。          pos\n",
       "2                                             还没安装，基本满意          pos\n",
       "3     电热水器收到了，京东自营商品就是好，发货速度快，品质有保障，安装效果好，宝贝非常喜欢，冬天可...          pos\n",
       "4     用了几次才来评价，对产品非常满意，加热快保温时间长，售后服务特别好，主动打电话询问送货情况帮...          pos\n",
       "...                                                 ...          ...\n",
       "1995                                差评，差的一塌糊涂，千万别买，上当了，          neg\n",
       "1996  热水器还没有安装，就搞一肚子气，安装人员今天推明天，明天推后天，售后安装服务太差，给差评，目...          neg\n",
       "1997                                        好不容易网购一下还漏电          neg\n",
       "1998                           东西送的挺快，后期报装2天还没人联系我，售后太差          neg\n",
       "1999                               买了两个，送到一个，还有一个至今未送到。          neg\n",
       "\n",
       "[1974 rows x 2 columns]"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reviews"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "b0621dd6-dc1c-481f-956d-db5c33d6a74f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       东西收到这么久，都忘了去好评，美的大品牌，值得信赖，东西整体来看，个人感觉还不错，没有出现什...\n",
       "1                                    安装师傅很给力，热水器也好用，感谢美的。\n",
       "2                                               还没安装，基本满意\n",
       "3       电热水器收到了，京东自营商品就是好，发货速度快，品质有保障，安装效果好，宝贝非常喜欢，冬天可...\n",
       "4       用了几次才来评价，对产品非常满意，加热快保温时间长，售后服务特别好，主动打电话询问送货情况帮...\n",
       "                              ...                        \n",
       "1995                                  差评，差的一塌糊涂，千万别买，上当了，\n",
       "1996    热水器还没有安装，就搞一肚子气，安装人员今天推明天，明天推后天，售后安装服务太差，给差评，目...\n",
       "1997                                          好不容易网购一下还漏电\n",
       "1998                             东西送的挺快，后期报装2天还没人联系我，售后太差\n",
       "1999                                 买了两个，送到一个，还有一个至今未送到。\n",
       "Name: content, Length: 1974, dtype: object"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "content "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "16f7b047-d5ad-440f-8c2d-f7fd259664a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 去除英文、数字、京东、美的、电热水器等词语\n",
    "strinfo = re.compile('[0-9a-zA-Z]|京东|美的|电热水器|热水器|')\n",
    "content = content.apply(lambda x: strinfo.sub('',x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "457317fe-a040-4f44-bce0-01b78fa812dd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "re.compile(r'[0-9a-zA-Z]|京东|美的|电热水器|热水器|', re.UNICODE)"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "strinfo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "50bab812-f9cc-4d6a-b72a-070333a0ffa6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       东西收到这么久，都忘了去好评，大品牌，值得信赖，东西整体来看，个人感觉还不错，没有出现什么问...\n",
       "1                                         安装师傅很给力，也好用，感谢。\n",
       "2                                               还没安装，基本满意\n",
       "3       收到了，自营商品就是好，发货速度快，品质有保障，安装效果好，宝贝非常喜欢，冬天可以小时有热水...\n",
       "4       用了几次才来评价，对产品非常满意，加热快保温时间长，售后服务特别好，主动打电话询问送货情况帮...\n",
       "                              ...                        \n",
       "1995                                  差评，差的一塌糊涂，千万别买，上当了，\n",
       "1996    还没有安装，就搞一肚子气，安装人员今天推明天，明天推后天，售后安装服务太差，给差评，目前还在...\n",
       "1997                                          好不容易网购一下还漏电\n",
       "1998                              东西送的挺快，后期报装天还没人联系我，售后太差\n",
       "1999                                 买了两个，送到一个，还有一个至今未送到。\n",
       "Name: content, Length: 1974, dtype: object"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "48fdd45c-5caa-4d91-8348-e9fceba33f94",
   "metadata": {},
   "outputs": [],
   "source": [
    "import jieba.posseg as psg\n",
    "import pandas as pd\n",
    "# 分词\n",
    "worker = lambda s: [(x.word, x.flag) for x in psg.cut(s)] # 自定义简单分词函数\n",
    "seg_word = content.apply(worker)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "8d2a786f-00f9-4e55-b436-f512ad6c74ae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       [(东西, ns), (收到, v), (这么久, r), (，, x), (都, d), ...\n",
       "1       [(安装, v), (师傅, nr), (很, d), (给, p), (力, n), (，...\n",
       "2       [(还, d), (没, v), (安装, v), (，, x), (基本, n), (满意...\n",
       "3       [(收到, v), (了, ul), (，, x), (自营, vn), (商品, n), ...\n",
       "4       [(用, p), (了, ul), (几次, m), (才, d), (来, v), (评价...\n",
       "                              ...                        \n",
       "1995    [(差, a), (评, n), (，, x), (差, a), (的, uj), (一塌糊...\n",
       "1996    [(还, d), (没有, v), (安装, v), (，, x), (就, d), (搞,...\n",
       "1997      [(好不容易, l), (网购, n), (一下, m), (还, d), (漏电, nz)]\n",
       "1998    [(东西, ns), (送, v), (的, uj), (挺快, v), (，, x), (...\n",
       "1999    [(买, v), (了, ul), (两个, m), (，, x), (送到, v), (一...\n",
       "Name: content, Length: 1974, dtype: object"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "seg_word"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "c3a9b655-2746-40b8-ade5-796ce22a834a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 将词语转为数据框形式，一列是词，一列是词语所在的句子ID，最后一列是词语在该句子的位置\n",
    "n_word = seg_word.apply(lambda x: len(x))  # 每一评论中词的个数\n",
    "n_content = [[x+1]*y for x,y in zip(list(seg_word.index), list(n_word))]\n",
    "# 将嵌套的列表展开，作为词所在评论的id\n",
    "index_content = sum(n_content, [])\n",
    "\n",
    "seg_word = sum(seg_word, [])\n",
    "# 词\n",
    "word = [x[0] for x in seg_word]\n",
    "# 词性\n",
    "nature = [x[1] for x in seg_word]\n",
    "content_type = [[x]*y for x,y in zip(list(reviews['content_type']), list(n_word))]\n",
    "# 评论类型\n",
    "content_type = sum(content_type, [])\n",
    "result = pd.DataFrame({\"index_content\":index_content, \n",
    "                       \"word\":word,\n",
    "                       \"nature\":nature,\n",
    "                       \"content_type\":content_type})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "02557913-c869-41aa-901b-49d07c6d1760",
   "metadata": {},
   "outputs": [
    {
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       "      <td>neg</td>\n",
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       "</table>\n",
       "<p>63794 rows × 4 columns</p>\n",
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      ],
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       "       index_content word nature content_type\n",
       "0                  1   东西     ns          pos\n",
       "1                  1   收到      v          pos\n",
       "2                  1  这么久      r          pos\n",
       "3                  1    ，      x          pos\n",
       "4                  1    都      d          pos\n",
       "...              ...  ...    ...          ...\n",
       "63789           2000   一个      m          neg\n",
       "63790           2000   至今      d          neg\n",
       "63791           2000    未      d          neg\n",
       "63792           2000   送到      v          neg\n",
       "63793           2000    。      x          neg\n",
       "\n",
       "[63794 rows x 4 columns]"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
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   "cell_type": "code",
   "execution_count": 79,
   "id": "3996758e-498b-48c6-90ea-bdb90fb8dfcb",
   "metadata": {},
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       "<p>51436 rows × 4 columns</p>\n",
       "</div>"
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      "text/plain": [
       "       index_content word nature content_type\n",
       "0                  1   东西     ns          pos\n",
       "1                  1   收到      v          pos\n",
       "2                  1  这么久      r          pos\n",
       "4                  1    都      d          pos\n",
       "5                  1    忘      v          pos\n",
       "...              ...  ...    ...          ...\n",
       "63788           2000   还有      v          neg\n",
       "63789           2000   一个      m          neg\n",
       "63790           2000   至今      d          neg\n",
       "63791           2000    未      d          neg\n",
       "63792           2000   送到      v          neg\n",
       "\n",
       "[51436 rows x 4 columns]"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 删除标点符号\n",
    "result = result[result['nature'] != 'x']\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "44e34046-9274-460b-ba24-652dc9c78bcb",
   "metadata": {},
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       "<p>25172 rows × 4 columns</p>\n",
       "</div>"
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      "text/plain": [
       "       index_content word nature content_type\n",
       "0                  1   东西     ns          pos\n",
       "1                  1   收到      v          pos\n",
       "2                  1  这么久      r          pos\n",
       "5                  1    忘      v          pos\n",
       "8                  1   好评      v          pos\n",
       "...              ...  ...    ...          ...\n",
       "63780           1999    差      a          neg\n",
       "63783           2000   两个      m          neg\n",
       "63785           2000   送到      v          neg\n",
       "63791           2000    未      d          neg\n",
       "63792           2000   送到      v          neg\n",
       "\n",
       "[25172 rows x 4 columns]"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 删除停用词\n",
    "# 加载停用词\n",
    "stop_path = open(\"D:/Users/19202/Desktop/stoplist.txt\",'r',encoding='utf-8')\n",
    "stop = [x.replace('\\n','') for x in stop_path.readlines()]\n",
    "# 得到非停用词序列\n",
    "word = list(set(word) - set(stop))\n",
    "# 判断表格中的单词列是否在非停用词列中\n",
    "result = result[result['word'].isin(word)]\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "e0d96ded-b1b9-49f6-b4f5-f6aa701209e7",
   "metadata": {},
   "outputs": [
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       "      <td>v</td>\n",
       "      <td>neg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24278</th>\n",
       "      <td>1999</td>\n",
       "      <td>售后</td>\n",
       "      <td>n</td>\n",
       "      <td>neg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24279</th>\n",
       "      <td>1999</td>\n",
       "      <td>太</td>\n",
       "      <td>d</td>\n",
       "      <td>neg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24280</th>\n",
       "      <td>1999</td>\n",
       "      <td>差</td>\n",
       "      <td>a</td>\n",
       "      <td>neg</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>24281 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       index_content word nature content_type\n",
       "0                  1   东西     ns          pos\n",
       "1                  1   收到      v          pos\n",
       "2                  1  这么久      r          pos\n",
       "3                  1    忘      v          pos\n",
       "4                  1   好评      v          pos\n",
       "...              ...  ...    ...          ...\n",
       "24276           1999    天      q          neg\n",
       "24277           1999   没人      v          neg\n",
       "24278           1999   售后      n          neg\n",
       "24279           1999    太      d          neg\n",
       "24280           1999    差      a          neg\n",
       "\n",
       "[24281 rows x 4 columns]"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 提取含名词的评论的句子id\n",
    "ind = result[[x == 'n' for x in result['nature']]]['index_content'].unique()\n",
    "# 提取评论\n",
    "result = result[result['index_content'].isin(ind)]\n",
    "# 重置索引\n",
    "result.reset_index(drop=True,inplace=True)\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "8d2d726f-56a1-4202-ae12-dbed24df0ba6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: wordcloud in c:\\anaconda\\lib\\site-packages (1.9.4)\n",
      "Requirement already satisfied: numpy>=1.6.1 in c:\\anaconda\\lib\\site-packages (from wordcloud) (1.26.4)\n",
      "Requirement already satisfied: pillow in c:\\anaconda\\lib\\site-packages (from wordcloud) (10.3.0)\n",
      "Requirement already satisfied: matplotlib in c:\\anaconda\\lib\\site-packages (from wordcloud) (3.8.4)\n",
      "Requirement already satisfied: contourpy>=1.0.1 in c:\\anaconda\\lib\\site-packages (from matplotlib->wordcloud) (1.2.0)\n",
      "Requirement already satisfied: cycler>=0.10 in c:\\anaconda\\lib\\site-packages (from matplotlib->wordcloud) (0.11.0)\n",
      "Requirement already satisfied: fonttools>=4.22.0 in c:\\anaconda\\lib\\site-packages (from matplotlib->wordcloud) (4.51.0)\n",
      "Requirement already satisfied: kiwisolver>=1.3.1 in c:\\anaconda\\lib\\site-packages (from matplotlib->wordcloud) (1.4.4)\n",
      "Requirement already satisfied: packaging>=20.0 in c:\\anaconda\\lib\\site-packages (from matplotlib->wordcloud) (23.2)\n",
      "Requirement already satisfied: pyparsing>=2.3.1 in c:\\anaconda\\lib\\site-packages (from matplotlib->wordcloud) (3.0.9)\n",
      "Requirement already satisfied: python-dateutil>=2.7 in c:\\anaconda\\lib\\site-packages (from matplotlib->wordcloud) (2.9.0.post0)\n",
      "Requirement already satisfied: six>=1.5 in c:\\anaconda\\lib\\site-packages (from python-dateutil>=2.7->matplotlib->wordcloud) (1.16.0)\n"
     ]
    }
   ],
   "source": [
    "!pip install wordcloud"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "0fb73819-dc08-4e9c-bcba-d9af0969abc3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "ename": "PermissionError",
     "evalue": "[Errno 13] Permission denied: 'D:/Users/19202/Desktop/word.csv'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mPermissionError\u001b[0m                           Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[85], line 20\u001b[0m\n\u001b[0;32m     18\u001b[0m plt\u001b[38;5;241m.\u001b[39mshow()\n\u001b[0;32m     19\u001b[0m  \u001b[38;5;66;03m# 将结果写出\u001b[39;00m\n\u001b[1;32m---> 20\u001b[0m result\u001b[38;5;241m.\u001b[39mto_csv(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mD:/Users/19202/Desktop/word.csv\u001b[39m\u001b[38;5;124m\"\u001b[39m, index \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m, encoding \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mutf-8\u001b[39m\u001b[38;5;124m'\u001b[39m)\n",
      "File \u001b[1;32mC:\\Anaconda\\Lib\\site-packages\\pandas\\util\\_decorators.py:333\u001b[0m, in \u001b[0;36mdeprecate_nonkeyword_arguments.<locals>.decorate.<locals>.wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    327\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(args) \u001b[38;5;241m>\u001b[39m num_allow_args:\n\u001b[0;32m    328\u001b[0m     warnings\u001b[38;5;241m.\u001b[39mwarn(\n\u001b[0;32m    329\u001b[0m         msg\u001b[38;5;241m.\u001b[39mformat(arguments\u001b[38;5;241m=\u001b[39m_format_argument_list(allow_args)),\n\u001b[0;32m    330\u001b[0m         \u001b[38;5;167;01mFutureWarning\u001b[39;00m,\n\u001b[0;32m    331\u001b[0m         stacklevel\u001b[38;5;241m=\u001b[39mfind_stack_level(),\n\u001b[0;32m    332\u001b[0m     )\n\u001b[1;32m--> 333\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m func(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "File \u001b[1;32mC:\\Anaconda\\Lib\\site-packages\\pandas\\core\\generic.py:3967\u001b[0m, in \u001b[0;36mNDFrame.to_csv\u001b[1;34m(self, path_or_buf, sep, na_rep, float_format, columns, header, index, index_label, mode, encoding, compression, quoting, quotechar, lineterminator, chunksize, date_format, doublequote, escapechar, decimal, errors, storage_options)\u001b[0m\n\u001b[0;32m   3956\u001b[0m df \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(\u001b[38;5;28mself\u001b[39m, ABCDataFrame) \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mto_frame()\n\u001b[0;32m   3958\u001b[0m formatter \u001b[38;5;241m=\u001b[39m DataFrameFormatter(\n\u001b[0;32m   3959\u001b[0m     frame\u001b[38;5;241m=\u001b[39mdf,\n\u001b[0;32m   3960\u001b[0m     header\u001b[38;5;241m=\u001b[39mheader,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   3964\u001b[0m     decimal\u001b[38;5;241m=\u001b[39mdecimal,\n\u001b[0;32m   3965\u001b[0m )\n\u001b[1;32m-> 3967\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m DataFrameRenderer(formatter)\u001b[38;5;241m.\u001b[39mto_csv(\n\u001b[0;32m   3968\u001b[0m     path_or_buf,\n\u001b[0;32m   3969\u001b[0m     lineterminator\u001b[38;5;241m=\u001b[39mlineterminator,\n\u001b[0;32m   3970\u001b[0m     sep\u001b[38;5;241m=\u001b[39msep,\n\u001b[0;32m   3971\u001b[0m     encoding\u001b[38;5;241m=\u001b[39mencoding,\n\u001b[0;32m   3972\u001b[0m     errors\u001b[38;5;241m=\u001b[39merrors,\n\u001b[0;32m   3973\u001b[0m     compression\u001b[38;5;241m=\u001b[39mcompression,\n\u001b[0;32m   3974\u001b[0m     quoting\u001b[38;5;241m=\u001b[39mquoting,\n\u001b[0;32m   3975\u001b[0m     columns\u001b[38;5;241m=\u001b[39mcolumns,\n\u001b[0;32m   3976\u001b[0m     index_label\u001b[38;5;241m=\u001b[39mindex_label,\n\u001b[0;32m   3977\u001b[0m     mode\u001b[38;5;241m=\u001b[39mmode,\n\u001b[0;32m   3978\u001b[0m     chunksize\u001b[38;5;241m=\u001b[39mchunksize,\n\u001b[0;32m   3979\u001b[0m     quotechar\u001b[38;5;241m=\u001b[39mquotechar,\n\u001b[0;32m   3980\u001b[0m     date_format\u001b[38;5;241m=\u001b[39mdate_format,\n\u001b[0;32m   3981\u001b[0m     doublequote\u001b[38;5;241m=\u001b[39mdoublequote,\n\u001b[0;32m   3982\u001b[0m     escapechar\u001b[38;5;241m=\u001b[39mescapechar,\n\u001b[0;32m   3983\u001b[0m     storage_options\u001b[38;5;241m=\u001b[39mstorage_options,\n\u001b[0;32m   3984\u001b[0m )\n",
      "File \u001b[1;32mC:\\Anaconda\\Lib\\site-packages\\pandas\\io\\formats\\format.py:1014\u001b[0m, in \u001b[0;36mDataFrameRenderer.to_csv\u001b[1;34m(self, path_or_buf, encoding, sep, columns, index_label, mode, compression, quoting, quotechar, lineterminator, chunksize, date_format, doublequote, escapechar, errors, storage_options)\u001b[0m\n\u001b[0;32m    993\u001b[0m     created_buffer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[0;32m    995\u001b[0m csv_formatter \u001b[38;5;241m=\u001b[39m CSVFormatter(\n\u001b[0;32m    996\u001b[0m     path_or_buf\u001b[38;5;241m=\u001b[39mpath_or_buf,\n\u001b[0;32m    997\u001b[0m     lineterminator\u001b[38;5;241m=\u001b[39mlineterminator,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   1012\u001b[0m     formatter\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mfmt,\n\u001b[0;32m   1013\u001b[0m )\n\u001b[1;32m-> 1014\u001b[0m csv_formatter\u001b[38;5;241m.\u001b[39msave()\n\u001b[0;32m   1016\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m created_buffer:\n\u001b[0;32m   1017\u001b[0m     \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(path_or_buf, StringIO)\n",
      "File \u001b[1;32mC:\\Anaconda\\Lib\\site-packages\\pandas\\io\\formats\\csvs.py:251\u001b[0m, in \u001b[0;36mCSVFormatter.save\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    247\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m    248\u001b[0m \u001b[38;5;124;03mCreate the writer & save.\u001b[39;00m\n\u001b[0;32m    249\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m    250\u001b[0m \u001b[38;5;66;03m# apply compression and byte/text conversion\u001b[39;00m\n\u001b[1;32m--> 251\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m get_handle(\n\u001b[0;32m    252\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mfilepath_or_buffer,\n\u001b[0;32m    253\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmode,\n\u001b[0;32m    254\u001b[0m     encoding\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mencoding,\n\u001b[0;32m    255\u001b[0m     errors\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39merrors,\n\u001b[0;32m    256\u001b[0m     compression\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcompression,\n\u001b[0;32m    257\u001b[0m     storage_options\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstorage_options,\n\u001b[0;32m    258\u001b[0m ) \u001b[38;5;28;01mas\u001b[39;00m handles:\n\u001b[0;32m    259\u001b[0m     \u001b[38;5;66;03m# Note: self.encoding is irrelevant here\u001b[39;00m\n\u001b[0;32m    260\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mwriter \u001b[38;5;241m=\u001b[39m csvlib\u001b[38;5;241m.\u001b[39mwriter(\n\u001b[0;32m    261\u001b[0m         handles\u001b[38;5;241m.\u001b[39mhandle,\n\u001b[0;32m    262\u001b[0m         lineterminator\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlineterminator,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    267\u001b[0m         quotechar\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mquotechar,\n\u001b[0;32m    268\u001b[0m     )\n\u001b[0;32m    270\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_save()\n",
      "File \u001b[1;32mC:\\Anaconda\\Lib\\site-packages\\pandas\\io\\common.py:873\u001b[0m, in \u001b[0;36mget_handle\u001b[1;34m(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options)\u001b[0m\n\u001b[0;32m    868\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(handle, \u001b[38;5;28mstr\u001b[39m):\n\u001b[0;32m    869\u001b[0m     \u001b[38;5;66;03m# Check whether the filename is to be opened in binary mode.\u001b[39;00m\n\u001b[0;32m    870\u001b[0m     \u001b[38;5;66;03m# Binary mode does not support 'encoding' and 'newline'.\u001b[39;00m\n\u001b[0;32m    871\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m ioargs\u001b[38;5;241m.\u001b[39mencoding \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mb\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m ioargs\u001b[38;5;241m.\u001b[39mmode:\n\u001b[0;32m    872\u001b[0m         \u001b[38;5;66;03m# Encoding\u001b[39;00m\n\u001b[1;32m--> 873\u001b[0m         handle \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mopen\u001b[39m(\n\u001b[0;32m    874\u001b[0m             handle,\n\u001b[0;32m    875\u001b[0m             ioargs\u001b[38;5;241m.\u001b[39mmode,\n\u001b[0;32m    876\u001b[0m             encoding\u001b[38;5;241m=\u001b[39mioargs\u001b[38;5;241m.\u001b[39mencoding,\n\u001b[0;32m    877\u001b[0m             errors\u001b[38;5;241m=\u001b[39merrors,\n\u001b[0;32m    878\u001b[0m             newline\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m    879\u001b[0m         )\n\u001b[0;32m    880\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m    881\u001b[0m         \u001b[38;5;66;03m# Binary mode\u001b[39;00m\n\u001b[0;32m    882\u001b[0m         handle \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mopen\u001b[39m(handle, ioargs\u001b[38;5;241m.\u001b[39mmode)\n",
      "\u001b[1;31mPermissionError\u001b[0m: [Errno 13] Permission denied: 'D:/Users/19202/Desktop/word.csv'"
     ]
    }
   ],
   "source": [
    "from wordcloud import WordCloud\n",
    "import matplotlib.pyplot as plt\n",
    " # 按word分组统计数目\n",
    "frequencies = result.groupby(by = ['word'])['word'].count()\n",
    " # 按数目降序排序\n",
    "frequencies = frequencies.sort_values(ascending = False)\n",
    " # 从文件中将图像读取为数组\n",
    "backgroud_Image=plt.imread(\"D:/Users/19202/Desktop/pl.jpg\")\n",
    "wordcloud = WordCloud(font_path=\"C:/Windows/Fonts/msyh.ttc\",\n",
    "                      max_words=100,\n",
    "                      background_color='white',\n",
    "                      mask=backgroud_Image)\n",
    "my_wordcloud = wordcloud.fit_words(frequencies)\n",
    " # 将数据展示到二维图像上\n",
    "plt.imshow(my_wordcloud)\n",
    " # 关掉x,y轴\n",
    "plt.axis('off') \n",
    "plt.show()\n",
    " # 将结果写出\n",
    "result.to_csv(\"D:/Users/19202/Desktop/word.csv\", index = False, encoding = 'utf-8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "58f7eb97-8c33-482d-838c-34b02ed7c6cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# 读入评论词表\n",
    "word = pd.read_csv(\"D:/Users/19202/Desktop/word.csv\", header=0)\n",
    "\n",
    "# 使用 pd.read_table 读取每行一个词语的文本文件\n",
    "pos_comment = pd.read_table(\"D:/Users/19202/Desktop/正面评价词语（中文）.txt\", header=None, encoding='utf-8')\n",
    "neg_comment = pd.read_table(\"D:/Users/19202/Desktop/负面评价词语（中文）.txt\", header=None, encoding='utf-8')\n",
    "pos_emotion = pd.read_table(\"D:/Users/19202/Desktop/正面情感词语（中文）.txt\", header=None, encoding='utf-8')\n",
    "neg_emotion = pd.read_table(\"D:/Users/19202/Desktop/负面情感词语（中文）.txt\", header=None, encoding='utf-8')\n",
    "\n",
    "# 合并情感词与评价词\n",
    "positive = set(pos_comment.iloc[:, 0]) | set(pos_emotion.iloc[:, 0])\n",
    "negative = set(neg_comment.iloc[:, 0]) | set(neg_emotion.iloc[:, 0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "a167a7b3-da02-4606-bdf7-a18b9ce165d6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 正负面情感词表中相同的词语\n",
    "intersection = positive & negative"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "a3c6e73b-6a6b-439b-8af9-262c3da32219",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'阴毒 ',\n",
       " '琐碎 ',\n",
       " '幽幽 ',\n",
       " '累牍连篇 ',\n",
       " '语无伦次 ',\n",
       " '心灰意懒 ',\n",
       " '凄切 ',\n",
       " '荒寂 ',\n",
       " '嫩 ',\n",
       " '背悔 ',\n",
       " '错误 ',\n",
       " '直盯盯 ',\n",
       " '面有愧色 ',\n",
       " '恼羞成怒 ',\n",
       " '迂腐 ',\n",
       " '渺 ',\n",
       " '不择手段 ',\n",
       " '懵里懵懂 ',\n",
       " '不成材 ',\n",
       " '害臊 ',\n",
       " '冗赘 ',\n",
       " '拉忽 ',\n",
       " '悲剧 ',\n",
       " '牛气 ',\n",
       " '乌烟瘴气 ',\n",
       " '将心比心 ',\n",
       " '怪罪 ',\n",
       " '明哲保身 ',\n",
       " '失悔 ',\n",
       " '轻蔑 ',\n",
       " '廉价',\n",
       " '呵 ',\n",
       " '迷离 ',\n",
       " '抠唆 ',\n",
       " '系念 ',\n",
       " '无道德观念 ',\n",
       " '清算 ',\n",
       " '摇摇晃晃 ',\n",
       " '黑森森 ',\n",
       " '爱搭不理 ',\n",
       " '恶煞煞 ',\n",
       " '凄凉 ',\n",
       " '懊 ',\n",
       " '可耻 ',\n",
       " '罪恶 ',\n",
       " '浇漓 ',\n",
       " '啰啰嗦嗦 ',\n",
       " '没有学问 ',\n",
       " '羊质虎皮 ',\n",
       " '满目疮痍 ',\n",
       " '油汪汪 ',\n",
       " '不可救药 ',\n",
       " '鸷悍 ',\n",
       " '羞愧 ',\n",
       " '老奸巨猾 ',\n",
       " '挤挤插插 ',\n",
       " '痴痴 ',\n",
       " '开小差 ',\n",
       " '薄 ',\n",
       " '无口才 ',\n",
       " '贼 ',\n",
       " '严重 ',\n",
       " '呆气 ',\n",
       " '冷销 ',\n",
       " '愁闷 ',\n",
       " '不消化 ',\n",
       " '假惺惺 ',\n",
       " '赝 ',\n",
       " '吆三喝四 ',\n",
       " '赤裸裸淫秽 ',\n",
       " '震惊 ',\n",
       " '闷气 ',\n",
       " '人头攒动 ',\n",
       " '烦神 ',\n",
       " '惊奇不已 ',\n",
       " '娇嫩 ',\n",
       " '没有头脑 ',\n",
       " '秽 ',\n",
       " '脾气暴 ',\n",
       " '家徒四壁 ',\n",
       " '娇贵 ',\n",
       " '喝斥 ',\n",
       " '不仁 ',\n",
       " '无涵养 ',\n",
       " '小里小气 ',\n",
       " '冥顽不化 ',\n",
       " '千钧一发 ',\n",
       " '松散散 ',\n",
       " '被动性 ',\n",
       " '雪上加霜 ',\n",
       " '诮 ',\n",
       " '卑 ',\n",
       " '黢 ',\n",
       " '谅 ',\n",
       " '惶惶然 ',\n",
       " '憋气 ',\n",
       " '恨入骨髓 ',\n",
       " '横 ',\n",
       " '不像话 ',\n",
       " '多病 ',\n",
       " '猖 ',\n",
       " '锋芒毕露 ',\n",
       " '寥寂 ',\n",
       " '险 ',\n",
       " '训诫 ',\n",
       " '强横 ',\n",
       " '詈 ',\n",
       " '太烂',\n",
       " '怆怳 ',\n",
       " '不公正 ',\n",
       " '怒 ',\n",
       " '吓人 ',\n",
       " '胶柱鼓瑟 ',\n",
       " '脾气坏 ',\n",
       " '吃后悔药 ',\n",
       " '戳壁脚 ',\n",
       " '骄气 ',\n",
       " '油煎火燎 ',\n",
       " '罪不容诛 ',\n",
       " '啼笑皆非 ',\n",
       " '急巴巴 ',\n",
       " '引咎 ',\n",
       " '迷迷茫茫 ',\n",
       " '乱真 ',\n",
       " '面带嗔色 ',\n",
       " '乌托邦 ',\n",
       " '目无余子 ',\n",
       " '唾骂 ',\n",
       " '缩头缩脑 ',\n",
       " '无力 ',\n",
       " '超然 ',\n",
       " '酸臭 ',\n",
       " '诞 ',\n",
       " '躁 ',\n",
       " '瘫软 ',\n",
       " '慊 ',\n",
       " '卑鄙无耻 ',\n",
       " '烟雾弥漫 ',\n",
       " '碌碌 ',\n",
       " '呆呆 ',\n",
       " '怨 ',\n",
       " '不宜居住 ',\n",
       " '庸俗 ',\n",
       " '圆滑 ',\n",
       " '孑 ',\n",
       " '残 ',\n",
       " '怒气冲冲 ',\n",
       " '惆怅 ',\n",
       " '荒诞无稽 ',\n",
       " '危亡 ',\n",
       " '欠完善 ',\n",
       " '玩忽 ',\n",
       " '左右两难 ',\n",
       " '率然 ',\n",
       " '丢魂 ',\n",
       " '贫瘠 ',\n",
       " '无关宏旨 ',\n",
       " '醉翁之意不在酒 ',\n",
       " '非分 ',\n",
       " '阴暗 ',\n",
       " '羞恶 ',\n",
       " '装腔 ',\n",
       " '指摘 ',\n",
       " '脏兮兮 ',\n",
       " '褊狭 ',\n",
       " '盲人瞎马 ',\n",
       " '必修 ',\n",
       " '畏首畏尾 ',\n",
       " '凶横 ',\n",
       " '过分简单化 ',\n",
       " '发憷 ',\n",
       " '架空 ',\n",
       " '怒气冲天 ',\n",
       " '焦急 ',\n",
       " '白搭 ',\n",
       " '贪婪 ',\n",
       " '赶尽杀绝 ',\n",
       " '气不忿 ',\n",
       " '灰茫茫 ',\n",
       " '不对称 ',\n",
       " '愚蒙 ',\n",
       " '心痛 ',\n",
       " '悔之不及 ',\n",
       " '易变 ',\n",
       " '没两下子 ',\n",
       " '枯槁 ',\n",
       " '乌洞洞 ',\n",
       " '食而不化 ',\n",
       " '怠惰 ',\n",
       " '惆 ',\n",
       " '悲恻 ',\n",
       " '急功近利 ',\n",
       " '隐隐 ',\n",
       " '赘 ',\n",
       " '错误百出 ',\n",
       " '缈 ',\n",
       " '冗余 ',\n",
       " '心急如火 ',\n",
       " '苍凉 ',\n",
       " '隔靴搔痒 ',\n",
       " '荒废 ',\n",
       " '气忿忿 ',\n",
       " '令人生厌 ',\n",
       " '私密 ',\n",
       " '毫无价值 ',\n",
       " '威 ',\n",
       " '怏然 ',\n",
       " '大动肝火 ',\n",
       " '臭名远扬 ',\n",
       " '打怵 ',\n",
       " '凶残 ',\n",
       " '悖逆 ',\n",
       " '心猿意马 ',\n",
       " '看不上眼 ',\n",
       " '恕 ',\n",
       " '郁郁寡欢 ',\n",
       " '枯 ',\n",
       " '义愤填膺 ',\n",
       " '令人费解 ',\n",
       " '不待见 ',\n",
       " '没关系 ',\n",
       " '白白 ',\n",
       " '凄然 ',\n",
       " '畏葸 ',\n",
       " '忘情 ',\n",
       " '封建 ',\n",
       " '圆 ',\n",
       " '蒙蒙 ',\n",
       " '缺德 ',\n",
       " '枉费心机 ',\n",
       " '勃然大怒 ',\n",
       " '骑虎难下 ',\n",
       " '撸 ',\n",
       " '伧 ',\n",
       " '低等 ',\n",
       " '害 ',\n",
       " '悖晦 ',\n",
       " '不分青红皂白 ',\n",
       " '媸 ',\n",
       " '愧恧 ',\n",
       " '褶 ',\n",
       " '驴唇不对马嘴 ',\n",
       " '引咎自责 ',\n",
       " '恟 ',\n",
       " '无关紧要 ',\n",
       " '忸 ',\n",
       " '冷冷 ',\n",
       " '反 ',\n",
       " '不好意思 ',\n",
       " '捉摸不定 ',\n",
       " '痛恶 ',\n",
       " '密 ',\n",
       " '掊击 ',\n",
       " '羡余 ',\n",
       " '不对茬儿 ',\n",
       " '刺鼻 ',\n",
       " '窘困 ',\n",
       " '背靠背 ',\n",
       " '腐恶 ',\n",
       " '肩摩毂击 ',\n",
       " '扭扭捏捏 ',\n",
       " '疾 ',\n",
       " '没有好脸 ',\n",
       " '诧异 ',\n",
       " '轻看 ',\n",
       " '没理 ',\n",
       " '黄色 ',\n",
       " '繁乱 ',\n",
       " '后悔 ',\n",
       " '漫无目的 ',\n",
       " '惨烈 ',\n",
       " '索然无味 ',\n",
       " '超重 ',\n",
       " '罪恶滔天 ',\n",
       " '打问号 ',\n",
       " '窒闷 ',\n",
       " '过不去 ',\n",
       " '二五眼 ',\n",
       " '心切 ',\n",
       " '心如刀割 ',\n",
       " '得鱼忘筌 ',\n",
       " '呆板 ',\n",
       " '惊疑 ',\n",
       " '碜 ',\n",
       " '扼腕 ',\n",
       " '剌戾 ',\n",
       " '墨 ',\n",
       " '硗薄 ',\n",
       " '毛躁 ',\n",
       " '怵头 ',\n",
       " '瞎 ',\n",
       " '怀疑 ',\n",
       " '不快 ',\n",
       " '怅惘 ',\n",
       " '惶恐 ',\n",
       " '溜号 ',\n",
       " '痛 ',\n",
       " '蛮悍 ',\n",
       " '怆恻 ',\n",
       " '可怜 ',\n",
       " '哀戚 ',\n",
       " '目瞪口呆 ',\n",
       " '惊异 ',\n",
       " '讥讪 ',\n",
       " '脾气爆躁 ',\n",
       " '短浅 ',\n",
       " '拖泥带水 ',\n",
       " '啬 ',\n",
       " '稗 ',\n",
       " '配不上 ',\n",
       " '惊怖 ',\n",
       " '冷嘲热讽 ',\n",
       " '痴 ',\n",
       " '劳而无功 ',\n",
       " '奸险 ',\n",
       " '使人疲劳 ',\n",
       " '令人厌恶 ',\n",
       " '难看 ',\n",
       " '顽钝 ',\n",
       " '辛 ',\n",
       " '獠 ',\n",
       " '满脸横肉 ',\n",
       " '势利眼 ',\n",
       " '说不过去 ',\n",
       " '刍 ',\n",
       " '不合理 ',\n",
       " '孩子气 ',\n",
       " '喧杂 ',\n",
       " '变相 ',\n",
       " '漆黑 ',\n",
       " '疑虑 ',\n",
       " '斥责 ',\n",
       " '破陋 ',\n",
       " '滞涩 ',\n",
       " '麻木不仁 ',\n",
       " '大失所望 ',\n",
       " '失礼 ',\n",
       " '捕风捉影 ',\n",
       " '正颜厉色 ',\n",
       " '愤愤然 ',\n",
       " '暗沉沉 ',\n",
       " '不精确 ',\n",
       " '冷血 ',\n",
       " '低级 ',\n",
       " '拥挤 ',\n",
       " '小气 ',\n",
       " '见风使舵 ',\n",
       " '不健康 ',\n",
       " '不努力 ',\n",
       " '缠手 ',\n",
       " '惊慌 ',\n",
       " '未列计划 ',\n",
       " '哀哀切切 ',\n",
       " '缛 ',\n",
       " '等闲视之 ',\n",
       " '隐秘 ',\n",
       " '不适应 ',\n",
       " '震悚 ',\n",
       " '顾忌 ',\n",
       " '忧思 ',\n",
       " '悖谬 ',\n",
       " '不近人情 ',\n",
       " '主观上 ',\n",
       " '呼幺喝六 ',\n",
       " '讆 ',\n",
       " '令人恶心 ',\n",
       " '苦闷 ',\n",
       " '朝不保夕 ',\n",
       " '迂拙 ',\n",
       " '不起眼 ',\n",
       " '不满 ',\n",
       " '琐 ',\n",
       " '气盛 ',\n",
       " '身无分文 ',\n",
       " '徒劳 ',\n",
       " '傲岸 ',\n",
       " '不屑 ',\n",
       " '挤巴 ',\n",
       " '色情 ',\n",
       " '死一般 ',\n",
       " '油渍渍 ',\n",
       " '颛蒙 ',\n",
       " '体谅 ',\n",
       " '凿空 ',\n",
       " '不是味儿 ',\n",
       " '惶悚 ',\n",
       " '忸忸怩怩 ',\n",
       " '愧疚 ',\n",
       " '踟躇 ',\n",
       " '愁 ',\n",
       " '牵念 ',\n",
       " '张口结舌 ',\n",
       " '花心 ',\n",
       " '超常 ',\n",
       " '悬 ',\n",
       " '单薄 ',\n",
       " '罪恶深重 ',\n",
       " '淫邪 ',\n",
       " '小瞧 ',\n",
       " '垃圾',\n",
       " '兔死狐悲 ',\n",
       " '半新不旧 ',\n",
       " '不修边幅 ',\n",
       " '荒僻 ',\n",
       " '官僚主义 ',\n",
       " '空幻 ',\n",
       " '特困 ',\n",
       " '刻舟求剑 ',\n",
       " '没味 ',\n",
       " '失宜 ',\n",
       " '瞪眼 ',\n",
       " '犹犹豫豫 ',\n",
       " '颠连 ',\n",
       " '泄气 ',\n",
       " '短视 ',\n",
       " '孤立无援 ',\n",
       " '死气沉沉 ',\n",
       " '铁公鸡一毛不拔 ',\n",
       " '无表情 ',\n",
       " '凶 ',\n",
       " '很烂',\n",
       " '过了气 ',\n",
       " '不宽容 ',\n",
       " '蛮横 ',\n",
       " '昏聩 ',\n",
       " '恶劣',\n",
       " '清冷 ',\n",
       " '气粗 ',\n",
       " '看风使舵 ',\n",
       " '杂乱无章 ',\n",
       " '多有微词 ',\n",
       " '馁 ',\n",
       " '变化万千 ',\n",
       " '脏乱差 ',\n",
       " '庸 ',\n",
       " '无光泽 ',\n",
       " '僭 ',\n",
       " '恤 ',\n",
       " '火烧火燎 ',\n",
       " '所谓 ',\n",
       " '惨 ',\n",
       " '厌恨 ',\n",
       " '轻浮 ',\n",
       " '悻悻然 ',\n",
       " '杀人如麻 ',\n",
       " '挂名 ',\n",
       " '狂 ',\n",
       " '不祥 ',\n",
       " '心胸狭隘 ',\n",
       " '贸然 ',\n",
       " '恣肆 ',\n",
       " '泼 ',\n",
       " '铺张 ',\n",
       " '忿忿不平 ',\n",
       " '不对头 ',\n",
       " '漫无边际 ',\n",
       " '跅弛 ',\n",
       " '品头论足 ',\n",
       " '废物 ',\n",
       " '惊叹 ',\n",
       " '零零碎碎 ',\n",
       " '灰色 ',\n",
       " '火头上 ',\n",
       " '土头土脑 ',\n",
       " '漏洞百出 ',\n",
       " '白衣苍狗 ',\n",
       " '恼火 ',\n",
       " '从心所欲 ',\n",
       " '假装神圣 ',\n",
       " '不痛不痒 ',\n",
       " '惊人 ',\n",
       " '暗中 ',\n",
       " '差可 ',\n",
       " '低智 ',\n",
       " '狷急 ',\n",
       " '柔肠百结 ',\n",
       " '颓 ',\n",
       " '憋着一肚子气 ',\n",
       " '过时 ',\n",
       " '悲酸 ',\n",
       " '愤愤 ',\n",
       " '恶贯满盈 ',\n",
       " '无能 ',\n",
       " '哀恸 ',\n",
       " '数落 ',\n",
       " '强行 ',\n",
       " '昏乱 ',\n",
       " '以怨报德 ',\n",
       " '打入冷宫 ',\n",
       " '茕茕孑立 ',\n",
       " '发愁 ',\n",
       " '茫茫然 ',\n",
       " '惛 ',\n",
       " '不对 ',\n",
       " '孤寂 ',\n",
       " '坡 ',\n",
       " '见怪 ',\n",
       " '不名一文 ',\n",
       " '一怒之下 ',\n",
       " '败兴 ',\n",
       " '笨 ',\n",
       " '酥软 ',\n",
       " '窘迫 ',\n",
       " '漫骂 ',\n",
       " '呵叱 ',\n",
       " '生气 ',\n",
       " '不尽如人意 ',\n",
       " '不开化 ',\n",
       " '手头紧 ',\n",
       " '自豪 ',\n",
       " '腐朽没落 ',\n",
       " '丧心病狂 ',\n",
       " '零七八碎 ',\n",
       " '索然寡味 ',\n",
       " '睁一只眼闭一只眼 ',\n",
       " '原 ',\n",
       " '懑 ',\n",
       " '愚笨 ',\n",
       " '盘陁 ',\n",
       " '幻 ',\n",
       " '不力 ',\n",
       " '置之不顾 ',\n",
       " '不妙 ',\n",
       " '诡 ',\n",
       " '瞢 ',\n",
       " '怅然若失 ',\n",
       " '好烂',\n",
       " '离题 ',\n",
       " '竦 ',\n",
       " '睁一眼闭一眼 ',\n",
       " '不得体 ',\n",
       " '暴虐 ',\n",
       " '繁缛 ',\n",
       " '禽兽不如 ',\n",
       " '不稳定 ',\n",
       " '偏颇 ',\n",
       " '踌躇 ',\n",
       " '过分拥挤 ',\n",
       " '家贫如洗 ',\n",
       " '够戗 ',\n",
       " '懒惰 ',\n",
       " '颐指气使 ',\n",
       " '魂不附体 ',\n",
       " '偏听偏信 ',\n",
       " '乌压压 ',\n",
       " '菲 ',\n",
       " '独断 ',\n",
       " '貌似强大 ',\n",
       " '顽固 ',\n",
       " '窳 ',\n",
       " '惶惧 ',\n",
       " '胡乱 ',\n",
       " '前呼后拥 ',\n",
       " '瞧不起 ',\n",
       " '气短 ',\n",
       " '脏乎乎 ',\n",
       " '踟 ',\n",
       " '落套 ',\n",
       " '害怕 ',\n",
       " '惶然不安 ',\n",
       " '詈骂 ',\n",
       " '红眼 ',\n",
       " '多义 ',\n",
       " '抠门儿 ',\n",
       " '未老先衰 ',\n",
       " '战兢兢 ',\n",
       " '炸 ',\n",
       " '死板 ',\n",
       " '僻静 ',\n",
       " '心狠手辣 ',\n",
       " '无益 ',\n",
       " '隐身 ',\n",
       " '无目的 ',\n",
       " '神气活现 ',\n",
       " '手无缚鸡之力 ',\n",
       " '责怨 ',\n",
       " '挂一漏万 ',\n",
       " '机械性 ',\n",
       " '浇薄 ',\n",
       " '含糊 ',\n",
       " '不足挂齿 ',\n",
       " '形影相吊 ',\n",
       " '进退维谷 ',\n",
       " '后怕 ',\n",
       " '欺诈性 ',\n",
       " '穷苦 ',\n",
       " '火急火燎 ',\n",
       " '黠 ',\n",
       " '心急 ',\n",
       " '锱铢必较 ',\n",
       " '太差',\n",
       " '心毒 ',\n",
       " '坏情 ',\n",
       " '流气 ',\n",
       " '同病相怜 ',\n",
       " '不正派 ',\n",
       " '拘束 ',\n",
       " '苛察 ',\n",
       " '非礼 ',\n",
       " '非生产性 ',\n",
       " '戆头戆脑 ',\n",
       " '不适宜 ',\n",
       " '萧森 ',\n",
       " '断魂 ',\n",
       " '恍惚 ',\n",
       " '厝火积薪 ',\n",
       " '污秽 ',\n",
       " '瘆 ',\n",
       " '暗黑 ',\n",
       " '不胜 ',\n",
       " '两面光 ',\n",
       " '不理智 ',\n",
       " '不客气 ',\n",
       " '滞销 ',\n",
       " '松散 ',\n",
       " '慵懒 ',\n",
       " '惘然 ',\n",
       " '风骚 ',\n",
       " '自负 ',\n",
       " '孤孤单单 ',\n",
       " '死沉沉 ',\n",
       " '诟 ',\n",
       " '恐 ',\n",
       " '令人窒息 ',\n",
       " '吃不准 ',\n",
       " '彷 ',\n",
       " '灯红酒绿 ',\n",
       " '挤得水泄不通 ',\n",
       " '掉以轻心 ',\n",
       " '骂得狗血喷头 ',\n",
       " '心酸 ',\n",
       " '愣神儿 ',\n",
       " '不周到 ',\n",
       " '笨手笨脚 ',\n",
       " '翻然悔悟 ',\n",
       " '乖僻 ',\n",
       " '涩苦 ',\n",
       " '为人作嫁 ',\n",
       " '逆 ',\n",
       " '会来事 ',\n",
       " '自恃 ',\n",
       " '猥亵 ',\n",
       " '险峭 ',\n",
       " '难堪 ',\n",
       " '谪 ',\n",
       " '闵 ',\n",
       " '无视 ',\n",
       " '懒得 ',\n",
       " '心惊肉跳 ',\n",
       " '繁复 ',\n",
       " '哭丧着脸 ',\n",
       " '丑恶 ',\n",
       " '有伤风化 ',\n",
       " '颟顸 ',\n",
       " '死心眼 ',\n",
       " '烦恼 ',\n",
       " '示不满 ',\n",
       " '难闻 ',\n",
       " '低沉 ',\n",
       " '挂火 ',\n",
       " '羞涩 ',\n",
       " '无特色 ',\n",
       " '庸庸碌碌 ',\n",
       " '闷 ',\n",
       " '好慢',\n",
       " '恕宥 ',\n",
       " '错综 ',\n",
       " '臭名昭著 ',\n",
       " '粗陋 ',\n",
       " '可叹 ',\n",
       " '枉然 ',\n",
       " '芜 ',\n",
       " '逾分 ',\n",
       " '装模作样 ',\n",
       " '佻 ',\n",
       " '不清洁 ',\n",
       " '有点旧 ',\n",
       " '受窘 ',\n",
       " '挑毛病 ',\n",
       " '幽晦 ',\n",
       " '猫哭老鼠 ',\n",
       " '不合宜 ',\n",
       " '兔死狗烹 ',\n",
       " '自相矛盾 ',\n",
       " '闷闷不乐 ',\n",
       " '索 ',\n",
       " '骄纵 ',\n",
       " '价格不菲 ',\n",
       " '淡漠 ',\n",
       " '捶胸顿足 ',\n",
       " '杂沓 ',\n",
       " '惼 ',\n",
       " '不友好 ',\n",
       " '斯文扫地 ',\n",
       " '见识短浅 ',\n",
       " '僵化 ',\n",
       " '冷淡 ',\n",
       " '厉声 ',\n",
       " '腥 ',\n",
       " '差评',\n",
       " '蹇 ',\n",
       " '猜忌 ',\n",
       " '疑惑 ',\n",
       " '目空一切 ',\n",
       " '偷偷 ',\n",
       " '作色 ',\n",
       " '不人道 ',\n",
       " '追悔莫及 ',\n",
       " '啷 ',\n",
       " '悲戚 ',\n",
       " '骇人听闻 ',\n",
       " '悠谬 ',\n",
       " '朦胧 ',\n",
       " '歉甚 ',\n",
       " '尖嘴薄舌 ',\n",
       " '岸然 ',\n",
       " '过当 ',\n",
       " '卖不掉 ',\n",
       " '过河拆桥 ',\n",
       " '大而化之 ',\n",
       " '危机四伏 ',\n",
       " '婆婆妈妈 ',\n",
       " '闹嚷嚷 ',\n",
       " '严苛 ',\n",
       " '不合时宜 ',\n",
       " '懦弱 ',\n",
       " '极度悲哀 ',\n",
       " '艰苦 ',\n",
       " '难人 ',\n",
       " '寡言 ',\n",
       " '怏怏不乐 ',\n",
       " '灰沉沉 ',\n",
       " '鄙俗 ',\n",
       " '错 ',\n",
       " '现行 ',\n",
       " '浮噪 ',\n",
       " '卑怯 ',\n",
       " '含怒 ',\n",
       " '怔 ',\n",
       " '不一致 ',\n",
       " '屈理 ',\n",
       " '一脸稚气 ',\n",
       " '喧噪 ',\n",
       " '放纵 ',\n",
       " '倥 ',\n",
       " '无精打采 ',\n",
       " '怜 ',\n",
       " '放诞 ',\n",
       " '臭气冲天 ',\n",
       " '缺心眼儿 ',\n",
       " '低劣 ',\n",
       " '残缺不全 ',\n",
       " '拘执 ',\n",
       " '老赶 ',\n",
       " '歪斜 ',\n",
       " '鸣冤叫屈 ',\n",
       " '悻悻 ',\n",
       " '拉不下脸来 ',\n",
       " '红脸 ',\n",
       " '纷乱 ',\n",
       " '恚愤 ',\n",
       " '凄迷 ',\n",
       " '不雅 ',\n",
       " '高价 ',\n",
       " '千疮百孔 ',\n",
       " '抱怨 ',\n",
       " '犯难 ',\n",
       " '臭哄哄 ',\n",
       " '辣鸡',\n",
       " '问心有愧 ',\n",
       " '憋拗 ',\n",
       " '孤单单 ',\n",
       " '恬淡 ',\n",
       " '白忙活儿 ',\n",
       " '潜 ',\n",
       " '凶悍 ',\n",
       " '下流 ',\n",
       " '小 ',\n",
       " '不合法 ',\n",
       " '变化不定 ',\n",
       " '坑人',\n",
       " '骇愕 ',\n",
       " '屁滚尿流 ',\n",
       " '急不可待 ',\n",
       " '虚弱 ',\n",
       " '三心二意 ',\n",
       " '保守 ',\n",
       " '荒淫 ',\n",
       " '愣住 ',\n",
       " '憾 ',\n",
       " '揭不开锅 ',\n",
       " '坑洼不平 ',\n",
       " '冗长 ',\n",
       " '赖 ',\n",
       " '轻狂 ',\n",
       " '生 ',\n",
       " '小心眼儿 ',\n",
       " '烦 ',\n",
       " '浮光掠影 ',\n",
       " '假仁假义 ',\n",
       " '惦挂 ',\n",
       " '不光明 ',\n",
       " '灰朦朦 ',\n",
       " '油乎乎 ',\n",
       " '怪 ',\n",
       " '惝恍 ',\n",
       " '嘲骂 ',\n",
       " '未成熟 ',\n",
       " '道德败坏 ',\n",
       " '忸怩作态 ',\n",
       " '悍然 ',\n",
       " '眼光短浅 ',\n",
       " '寡淡 ',\n",
       " '狠心 ',\n",
       " '狠劲 ',\n",
       " '艰苦卓绝 ',\n",
       " '名过其实 ',\n",
       " '忉 ',\n",
       " '虚荣 ',\n",
       " '阢 ',\n",
       " '变心 ',\n",
       " '褊急 ',\n",
       " '鸡毛蒜皮 ',\n",
       " '一锅粥 ',\n",
       " '心胆俱裂 ',\n",
       " '愣 ',\n",
       " '糊涂 ',\n",
       " '气势汹汹 ',\n",
       " '殷 ',\n",
       " '心惊胆战 ',\n",
       " '狗眼看人 ',\n",
       " '愚陋 ',\n",
       " '惊险 ',\n",
       " '荡 ',\n",
       " '凄寂 ',\n",
       " '不打紧 ',\n",
       " '穷奢极侈 ',\n",
       " '火爆 ',\n",
       " '吃力 ',\n",
       " '不可一世 ',\n",
       " '酷烈 ',\n",
       " '拈轻怕重 ',\n",
       " '云遮雾障 ',\n",
       " '变幻莫测 ',\n",
       " '杂草丛生 ',\n",
       " '臭名昭彰 ',\n",
       " '发狂 ',\n",
       " '恹 ',\n",
       " '怅怅 ',\n",
       " '荒淫无耻 ',\n",
       " '鼠胆 ',\n",
       " '低档 ',\n",
       " '魔怔 ',\n",
       " '荒弃 ',\n",
       " '不顾 ',\n",
       " '妖 ',\n",
       " '抱恨 ',\n",
       " '恚恨 ',\n",
       " '凶巴巴 ',\n",
       " '冥冥 ',\n",
       " '累赘 ',\n",
       " '利欲熏心 ',\n",
       " '看不顺眼 ',\n",
       " '老式 ',\n",
       " '有失身分 ',\n",
       " '邪 ',\n",
       " '不成话 ',\n",
       " '侉 ',\n",
       " '悱 ',\n",
       " '香艳 ',\n",
       " '不均匀 ',\n",
       " '冷清清 ',\n",
       " '纷繁 ',\n",
       " '诘 ',\n",
       " '拿腔拿调 ',\n",
       " '寂 ',\n",
       " '挑逗性 ',\n",
       " '万马齐喑 ',\n",
       " '回头 ',\n",
       " '愧赧 ',\n",
       " '可恶 ',\n",
       " '歪 ',\n",
       " '一无所长 ',\n",
       " '惧怕 ',\n",
       " '秽土 ',\n",
       " '苦恼 ',\n",
       " '平铺直叙 ',\n",
       " '不绝如缕 ',\n",
       " '执拗 ',\n",
       " '零碎 ',\n",
       " '四面楚歌 ',\n",
       " '挤 ',\n",
       " '厌弃 ',\n",
       " '冷冰冰 ',\n",
       " '骨鲠在喉 ',\n",
       " '悔不该 ',\n",
       " '凶狠 ',\n",
       " '肝肠寸断 ',\n",
       " '亏心 ',\n",
       " '暝 ',\n",
       " '心有余悸 ',\n",
       " '口头上 ',\n",
       " '酸涩 ',\n",
       " '大手大脚 ',\n",
       " '偏激 ',\n",
       " '膻气 ',\n",
       " '心烦 ',\n",
       " '怫然不悦 ',\n",
       " '遗憾 ',\n",
       " '单调 ',\n",
       " '群魔乱舞 ',\n",
       " '猥琐 ',\n",
       " '怜悯 ',\n",
       " '懊恼 ',\n",
       " '有碍观瞻 ',\n",
       " '追悔 ',\n",
       " '哓 ',\n",
       " '海底捞针 ',\n",
       " '反唇相讥 ',\n",
       " '高难度 ',\n",
       " '戾 ',\n",
       " '幽冥 ',\n",
       " '饶人 ',\n",
       " '焦心 ',\n",
       " '心狠 ',\n",
       " '辛辛苦苦 ',\n",
       " '惦 ',\n",
       " '轸 ',\n",
       " '无限制 ',\n",
       " '疣赘 ',\n",
       " '耳生 ',\n",
       " '虚惊 ',\n",
       " '嗔 ',\n",
       " '不可降解 ',\n",
       " '大骂 ',\n",
       " '凶毒 ',\n",
       " '失意 ',\n",
       " '犷悍 ',\n",
       " '随心所欲 ',\n",
       " '诡计多端 ',\n",
       " '险诈 ',\n",
       " '老弱病残 ',\n",
       " '陋 ',\n",
       " '变幻无常 ',\n",
       " '一文不值 ',\n",
       " '隐隐绰绰 ',\n",
       " '扎手 ',\n",
       " '不足轻重 ',\n",
       " '混交 ',\n",
       " '见异思迁 ',\n",
       " '松垮垮 ',\n",
       " '无知 ',\n",
       " '凹凸 ',\n",
       " '铺张浪费 ',\n",
       " '颛 ',\n",
       " '责 ',\n",
       " '低能 ',\n",
       " '哀愁 ',\n",
       " '愍 ',\n",
       " '怕生 ',\n",
       " '凛凛 ',\n",
       " '不合适 ',\n",
       " '虎头蛇尾 ',\n",
       " '悚 ',\n",
       " '反常 ',\n",
       " '怨恨 ',\n",
       " '惊奇 ',\n",
       " '寒伧 ',\n",
       " '动魄惊心 ',\n",
       " '赧颜 ',\n",
       " '假 ',\n",
       " '不共戴天 ',\n",
       " '矮 ',\n",
       " '不辨菽麦 ',\n",
       " '残毒 ',\n",
       " '充满危机 ',\n",
       " '无价值 ',\n",
       " '悭吝 ',\n",
       " '非法 ',\n",
       " '造次 ',\n",
       " '腐化 ',\n",
       " '不屑于 ',\n",
       " '极度悲伤 ',\n",
       " '尖酸刻薄 ',\n",
       " '连篇累牍 ',\n",
       " '令人折断腰 ',\n",
       " '萧 ',\n",
       " '愧对 ',\n",
       " '浅尝辄止 ',\n",
       " '厌倦 ',\n",
       " '无稽 ',\n",
       " '浑浊 ',\n",
       " '幕后 ',\n",
       " '阴沉 ',\n",
       " '不愿意 ',\n",
       " '大发雷霆 ',\n",
       " '无望 ',\n",
       " '干瘪瘪 ',\n",
       " '荒谬 ',\n",
       " '反叛 ',\n",
       " ...}"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "negative"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "7391d4c3-41ea-4d0d-8ae7-71064bf496ca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'严肃 ',\n",
       " '优柔 ',\n",
       " '偏 ',\n",
       " '傥 ',\n",
       " '僄 ',\n",
       " '僭 ',\n",
       " '儇 ',\n",
       " '冥 ',\n",
       " '刺眼 ',\n",
       " '剽悍 ',\n",
       " '华 ',\n",
       " '卑 ',\n",
       " '同情 ',\n",
       " '含蓄 ',\n",
       " '哙 ',\n",
       " '噲 ',\n",
       " '在乎 ',\n",
       " '大 ',\n",
       " '天真 ',\n",
       " '娆 ',\n",
       " '娇 ',\n",
       " '孛 ',\n",
       " '寂 ',\n",
       " '密 ',\n",
       " '小 ',\n",
       " '巧 ',\n",
       " '幽 ',\n",
       " '强 ',\n",
       " '心疼 ',\n",
       " '忌 ',\n",
       " '忮 ',\n",
       " '怃 ',\n",
       " '恂 ',\n",
       " '恣肆 ',\n",
       " '悍 ',\n",
       " '悚 ',\n",
       " '惜 ',\n",
       " '惨淡 ',\n",
       " '惨烈 ',\n",
       " '愀 ',\n",
       " '慊 ',\n",
       " '憨 ',\n",
       " '懔 ',\n",
       " '戾 ',\n",
       " '投机 ',\n",
       " '挂牵 ',\n",
       " '殷 ',\n",
       " '油汪汪 ',\n",
       " '泼辣 ',\n",
       " '浅 ',\n",
       " '涵蓄 ',\n",
       " '清淡 ',\n",
       " '滑 ',\n",
       " '满 ',\n",
       " '火 ',\n",
       " '火暴 ',\n",
       " '火爆 ',\n",
       " '烈 ',\n",
       " '狠 ',\n",
       " '狷 ',\n",
       " '玄 ',\n",
       " '率 ',\n",
       " '畏 ',\n",
       " '痴 ',\n",
       " '白 ',\n",
       " '硬 ',\n",
       " '窈冥 ',\n",
       " '竦 ',\n",
       " '笃 ',\n",
       " '简单 ',\n",
       " '粗放 ',\n",
       " '粗犷 ',\n",
       " '细 ',\n",
       " '老实 ',\n",
       " '老辣 ',\n",
       " '腻 ',\n",
       " '芜 ',\n",
       " '苦 ',\n",
       " '苦苦 ',\n",
       " '菀 ',\n",
       " '菲 ',\n",
       " '蔫不唧儿 ',\n",
       " '要紧 ',\n",
       " '豪 ',\n",
       " '贪 ',\n",
       " '轫 ',\n",
       " '软 ',\n",
       " '轻 ',\n",
       " '轻易 ',\n",
       " '郁 ',\n",
       " '酷 ',\n",
       " '重 ',\n",
       " '陋 ',\n",
       " '随便 ',\n",
       " '风流 ',\n",
       " '风风火火 ',\n",
       " '饶 ',\n",
       " '鬼 '}"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "intersection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "9c710b20-d87e-4ee8-826a-73dcf7cf8b87",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'严肃 ',\n",
       " '优柔 ',\n",
       " '偏 ',\n",
       " '傥 ',\n",
       " '僄 ',\n",
       " '僭 ',\n",
       " '儇 ',\n",
       " '冥 ',\n",
       " '刺眼 ',\n",
       " '剽悍 ',\n",
       " '华 ',\n",
       " '卑 ',\n",
       " '同情 ',\n",
       " '含蓄 ',\n",
       " '哙 ',\n",
       " '噲 ',\n",
       " '在乎 ',\n",
       " '大 ',\n",
       " '天真 ',\n",
       " '娆 ',\n",
       " '娇 ',\n",
       " '孛 ',\n",
       " '寂 ',\n",
       " '密 ',\n",
       " '小 ',\n",
       " '巧 ',\n",
       " '幽 ',\n",
       " '强 ',\n",
       " '心疼 ',\n",
       " '忌 ',\n",
       " '忮 ',\n",
       " '怃 ',\n",
       " '恂 ',\n",
       " '恣肆 ',\n",
       " '悍 ',\n",
       " '悚 ',\n",
       " '惜 ',\n",
       " '惨淡 ',\n",
       " '惨烈 ',\n",
       " '愀 ',\n",
       " '慊 ',\n",
       " '憨 ',\n",
       " '懔 ',\n",
       " '戾 ',\n",
       " '投机 ',\n",
       " '挂牵 ',\n",
       " '殷 ',\n",
       " '油汪汪 ',\n",
       " '泼辣 ',\n",
       " '浅 ',\n",
       " '涵蓄 ',\n",
       " '清淡 ',\n",
       " '滑 ',\n",
       " '满 ',\n",
       " '火 ',\n",
       " '火暴 ',\n",
       " '火爆 ',\n",
       " '烈 ',\n",
       " '狠 ',\n",
       " '狷 ',\n",
       " '玄 ',\n",
       " '率 ',\n",
       " '畏 ',\n",
       " '痴 ',\n",
       " '白 ',\n",
       " '硬 ',\n",
       " '窈冥 ',\n",
       " '竦 ',\n",
       " '笃 ',\n",
       " '简单 ',\n",
       " '粗放 ',\n",
       " '粗犷 ',\n",
       " '细 ',\n",
       " '老实 ',\n",
       " '老辣 ',\n",
       " '腻 ',\n",
       " '芜 ',\n",
       " '苦 ',\n",
       " '苦苦 ',\n",
       " '菀 ',\n",
       " '菲 ',\n",
       " '蔫不唧儿 ',\n",
       " '要紧 ',\n",
       " '豪 ',\n",
       " '贪 ',\n",
       " '轫 ',\n",
       " '软 ',\n",
       " '轻 ',\n",
       " '轻易 ',\n",
       " '郁 ',\n",
       " '酷 ',\n",
       " '重 ',\n",
       " '陋 ',\n",
       " '随便 ',\n",
       " '风流 ',\n",
       " '风风火火 ',\n",
       " '饶 ',\n",
       " '鬼 '}"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "intersection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "d06442a6-f4d3-46e2-a0c8-3a3b02ff0591",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['倜傥 ',\n",
       " '人寿年丰 ',\n",
       " '惺 ',\n",
       " '锃亮 ',\n",
       " '非常热心 ',\n",
       " '宜人 ',\n",
       " '喜悦 ',\n",
       " '圆熟 ',\n",
       " '炯 ',\n",
       " '刚直不阿 ',\n",
       " '阔 ',\n",
       " '崇尚 ',\n",
       " '赫赫有名 ',\n",
       " '上赶 ',\n",
       " '可心 ',\n",
       " '灵捷 ',\n",
       " '整齐划一 ',\n",
       " '簇新 ',\n",
       " '简 ',\n",
       " '考究 ',\n",
       " '怡然自得 ',\n",
       " '豪宕 ',\n",
       " '温静 ',\n",
       " '巴 ',\n",
       " '力主 ',\n",
       " '痴心不改 ',\n",
       " '赞慕 ',\n",
       " '特级 ',\n",
       " '史诗般 ',\n",
       " '啧啧称羡 ',\n",
       " '清丽 ',\n",
       " '辩证 ',\n",
       " '端正 ',\n",
       " '春秋正富 ',\n",
       " '尔雅 ',\n",
       " '爽朗 ',\n",
       " '葱茂 ',\n",
       " '理会 ',\n",
       " '痴迷 ',\n",
       " '友好 ',\n",
       " '横心 ',\n",
       " '省俭 ',\n",
       " '适意 ',\n",
       " '觥筹交错 ',\n",
       " '求实 ',\n",
       " '锐敏 ',\n",
       " '均匀 ',\n",
       " '铁 ',\n",
       " '好办 ',\n",
       " '高超 ',\n",
       " '率真 ',\n",
       " '大公无私 ',\n",
       " '妍丽 ',\n",
       " '鹤发童颜 ',\n",
       " '名声大 ',\n",
       " '喜幸 ',\n",
       " '碍事 ',\n",
       " '兴旺 ',\n",
       " '错落有致 ',\n",
       " '完备 ',\n",
       " '精到 ',\n",
       " '低调 ',\n",
       " '贤慧 ',\n",
       " '感谢',\n",
       " '熠耀 ',\n",
       " '松动 ',\n",
       " '景仰 ',\n",
       " '有价值 ',\n",
       " '靓丽 ',\n",
       " '机巧 ',\n",
       " '不费力 ',\n",
       " '安康 ',\n",
       " '明处 ',\n",
       " '熠熠生辉 ',\n",
       " '如醉如痴 ',\n",
       " '花容月貌 ',\n",
       " '毅然决然 ',\n",
       " '谐和 ',\n",
       " '奠祭 ',\n",
       " '翩翩 ',\n",
       " '扬眉吐气 ',\n",
       " '敦敦实实 ',\n",
       " '必需 ',\n",
       " '谢天谢地 ',\n",
       " '厚道 ',\n",
       " '气象万千 ',\n",
       " '苦心孤诣 ',\n",
       " '谦恭 ',\n",
       " '无牵无挂 ',\n",
       " '管事 ',\n",
       " '朝拜 ',\n",
       " '谦 ',\n",
       " '特出 ',\n",
       " '珍视 ',\n",
       " '敬 ',\n",
       " '光灿 ',\n",
       " '天随人愿 ',\n",
       " '深刻 ',\n",
       " '委婉 ',\n",
       " '聪明绝顶 ',\n",
       " '鞠躬 ',\n",
       " '百无一失 ',\n",
       " '紧凑 ',\n",
       " '称赏 ',\n",
       " '高深 ',\n",
       " '重在 ',\n",
       " '心醉 ',\n",
       " '眷爱 ',\n",
       " '悲壮 ',\n",
       " '当红 ',\n",
       " '妖娆 ',\n",
       " '浓香 ',\n",
       " '竭诚 ',\n",
       " '祝 ',\n",
       " '呼之欲出 ',\n",
       " '英烈 ',\n",
       " '智勇双全 ',\n",
       " '严谨 ',\n",
       " '落落大方 ',\n",
       " '实际 ',\n",
       " '豪情满怀 ',\n",
       " '利他 ',\n",
       " '厉害',\n",
       " '清澈 ',\n",
       " '淡雅 ',\n",
       " '见微知萌 ',\n",
       " '杰出 ',\n",
       " '仰 ',\n",
       " '清明 ',\n",
       " '合群 ',\n",
       " '秀外慧中 ',\n",
       " '天才 ',\n",
       " '朴素 ',\n",
       " '称道 ',\n",
       " '如花似玉 ',\n",
       " '不苟言笑 ',\n",
       " '路不拾遗 ',\n",
       " '谨慎 ',\n",
       " '虚怀若谷 ',\n",
       " '生死 ',\n",
       " '执著 ',\n",
       " '不限 ',\n",
       " '乖觉 ',\n",
       " '温馨 ',\n",
       " '单刀直入 ',\n",
       " '无毒 ',\n",
       " '豪迈 ',\n",
       " '宽怀 ',\n",
       " '昶 ',\n",
       " '娓娓动听 ',\n",
       " '壮丽 ',\n",
       " '说妥 ',\n",
       " '秀 ',\n",
       " '超群绝伦 ',\n",
       " '灵 ',\n",
       " '山摇地动 ',\n",
       " '健旺 ',\n",
       " '有文化 ',\n",
       " '恪 ',\n",
       " '翻天覆地 ',\n",
       " '划时代 ',\n",
       " '活泛 ',\n",
       " '嫉妒 ',\n",
       " '眼热 ',\n",
       " '楚楚可怜 ',\n",
       " '爱恋 ',\n",
       " '呱呱叫 ',\n",
       " '新颖 ',\n",
       " '亲热 ',\n",
       " '弘 ',\n",
       " '掏心 ',\n",
       " '美味可口 ',\n",
       " '懂事 ',\n",
       " '智 ',\n",
       " '纯洁 ',\n",
       " '清幽 ',\n",
       " '备细 ',\n",
       " '知冷知热 ',\n",
       " '有望 ',\n",
       " '旗帜鲜明 ',\n",
       " '泰然自若 ',\n",
       " '明灿灿 ',\n",
       " '坦诚相见 ',\n",
       " '宏 ',\n",
       " '玮 ',\n",
       " '踊跃 ',\n",
       " '澄碧 ',\n",
       " '头脑清醒 ',\n",
       " '勾魂摄魄 ',\n",
       " '少不得 ',\n",
       " '耳闻目睹 ',\n",
       " '热门 ',\n",
       " '免费 ',\n",
       " '令人钦佩 ',\n",
       " '柔顺 ',\n",
       " '乐意 ',\n",
       " '刚直 ',\n",
       " '端静 ',\n",
       " '肃静 ',\n",
       " '整洁 ',\n",
       " '威风凛凛 ',\n",
       " '疼惜 ',\n",
       " '琳琅满目 ',\n",
       " '手巧 ',\n",
       " '超群 ',\n",
       " '顺口 ',\n",
       " '诚 ',\n",
       " '受听 ',\n",
       " '醒目 ',\n",
       " '慎重 ',\n",
       " '烂漫 ',\n",
       " '热乎 ',\n",
       " '欲 ',\n",
       " '别具一格 ',\n",
       " '芊 ',\n",
       " '成熟 ',\n",
       " '坚忍 ',\n",
       " '超俗 ',\n",
       " '有头有脸 ',\n",
       " '无恙 ',\n",
       " '坚强 ',\n",
       " '稚弱 ',\n",
       " '豪华型 ',\n",
       " '滑不唧溜 ',\n",
       " '鸣谢 ',\n",
       " '给力',\n",
       " '高精度 ',\n",
       " '注重 ',\n",
       " '殷实 ',\n",
       " '容 ',\n",
       " '见多识广 ',\n",
       " '不亢不卑 ',\n",
       " '真格的 ',\n",
       " '应准 ',\n",
       " '石破天惊 ',\n",
       " '雄姿英发 ',\n",
       " '礼貌 ',\n",
       " '温和 ',\n",
       " '关照 ',\n",
       " '抢眼 ',\n",
       " '完美无疵 ',\n",
       " '昭然若揭 ',\n",
       " '心灵手巧 ',\n",
       " '美满 ',\n",
       " '廉洁奉公 ',\n",
       " '众口一词 ',\n",
       " '明人不做暗事 ',\n",
       " '茁 ',\n",
       " '冀 ',\n",
       " '警 ',\n",
       " '精神矍铄 ',\n",
       " '深入人心 ',\n",
       " '坚 ',\n",
       " '五星级 ',\n",
       " '一呼百诺 ',\n",
       " '豪壮 ',\n",
       " '肥 ',\n",
       " '千依百顺 ',\n",
       " '赞服 ',\n",
       " '娇艳 ',\n",
       " '缥 ',\n",
       " '历历可数 ',\n",
       " '通达 ',\n",
       " '美丽 ',\n",
       " '胜 ',\n",
       " '玄远 ',\n",
       " '忠顺 ',\n",
       " '哄闹 ',\n",
       " '扬扬 ',\n",
       " '整饬 ',\n",
       " '新 ',\n",
       " '风雨无阻 ',\n",
       " '熙 ',\n",
       " '活 ',\n",
       " '事关重大 ',\n",
       " '敏捷 ',\n",
       " '内秀 ',\n",
       " '强有力 ',\n",
       " '懂行 ',\n",
       " '经用 ',\n",
       " '有才干 ',\n",
       " '热和 ',\n",
       " '豁 ',\n",
       " '悦服 ',\n",
       " '和悦 ',\n",
       " '快慰 ',\n",
       " '弥足珍贵 ',\n",
       " '文明 ',\n",
       " '香馥馥 ',\n",
       " '果 ',\n",
       " '锬 ',\n",
       " '毫无问题 ',\n",
       " '可意 ',\n",
       " '鸿 ',\n",
       " '鲜 ',\n",
       " '神奥 ',\n",
       " '上流 ',\n",
       " '静寂 ',\n",
       " '超俗绝世 ',\n",
       " '奉若神明 ',\n",
       " '震撼人心 ',\n",
       " '神气 ',\n",
       " '雄 ',\n",
       " '秀气 ',\n",
       " '尊敬 ',\n",
       " '素洁 ',\n",
       " '灿然 ',\n",
       " '不容置疑 ',\n",
       " '欢喜 ',\n",
       " '均衡 ',\n",
       " '馥郁 ',\n",
       " '欣喜 ',\n",
       " '堂皇 ',\n",
       " '神通广大 ',\n",
       " '没有搀杂 ',\n",
       " '庆幸 ',\n",
       " '富 ',\n",
       " '光洁 ',\n",
       " '领情 ',\n",
       " '对号 ',\n",
       " '烁 ',\n",
       " '占理 ',\n",
       " '易如反掌 ',\n",
       " '芾 ',\n",
       " '定 ',\n",
       " '抖 ',\n",
       " '天翻地覆 ',\n",
       " '平等 ',\n",
       " '春风得意 ',\n",
       " '壮观 ',\n",
       " '重视 ',\n",
       " '年富力强 ',\n",
       " '通俗易懂 ',\n",
       " '曾经沧海 ',\n",
       " '柔美 ',\n",
       " '停妥 ',\n",
       " '毫不动摇 ',\n",
       " '精密 ',\n",
       " '祝愿 ',\n",
       " '平整 ',\n",
       " '略 ',\n",
       " '灏 ',\n",
       " '松快 ',\n",
       " '强大 ',\n",
       " '依允 ',\n",
       " '下酒 ',\n",
       " '亲昵 ',\n",
       " '忭 ',\n",
       " '豁然 ',\n",
       " '直捷 ',\n",
       " '轻轻 ',\n",
       " '叫真儿 ',\n",
       " '温厚 ',\n",
       " '美滋滋 ',\n",
       " '静悄 ',\n",
       " '创造性 ',\n",
       " '驯服 ',\n",
       " '祝贺 ',\n",
       " '浑然 ',\n",
       " '庄严 ',\n",
       " '渴求 ',\n",
       " '好吃 ',\n",
       " '敬服 ',\n",
       " '康健 ',\n",
       " '口角春风 ',\n",
       " '欣慰 ',\n",
       " '醇朴 ',\n",
       " '晶莹 ',\n",
       " '很有抱负 ',\n",
       " '致贺 ',\n",
       " '硬朗 ',\n",
       " '对味儿 ',\n",
       " '感 ',\n",
       " '坚挺 ',\n",
       " '宁静 ',\n",
       " '高档 ',\n",
       " '不容置辩 ',\n",
       " '倍儿棒 ',\n",
       " '科学 ',\n",
       " '赏罚严明 ',\n",
       " '甜蜜 ',\n",
       " '挑战性 ',\n",
       " '狠狠 ',\n",
       " '堪称一绝 ',\n",
       " '利害攸关 ',\n",
       " '慈悲 ',\n",
       " '属意 ',\n",
       " '敢 ',\n",
       " '调和 ',\n",
       " '毫不利己 ',\n",
       " '真诚 ',\n",
       " '悦耳 ',\n",
       " '迎刃而解 ',\n",
       " '馐 ',\n",
       " '宓 ',\n",
       " '爱怜 ',\n",
       " '善始善终 ',\n",
       " '甲级 ',\n",
       " '是 ',\n",
       " '实事求是 ',\n",
       " '准期 ',\n",
       " '头头是道 ',\n",
       " '温文尔雅 ',\n",
       " '春色满园 ',\n",
       " '不会弄错 ',\n",
       " '泼悍 ',\n",
       " '破釜沉舟 ',\n",
       " '万马奔腾 ',\n",
       " '明晰 ',\n",
       " '雄壮 ',\n",
       " '侠义 ',\n",
       " '无偿 ',\n",
       " '清澈见底 ',\n",
       " '虚己 ',\n",
       " '芳 ',\n",
       " '基本 ',\n",
       " '有礼貌 ',\n",
       " '圣礼 ',\n",
       " '满面春风 ',\n",
       " '确 ',\n",
       " '前程似锦 ',\n",
       " '秀雅 ',\n",
       " '入魔 ',\n",
       " '叹赏 ',\n",
       " '首要 ',\n",
       " '秀俊 ',\n",
       " '决绝 ',\n",
       " '基础 ',\n",
       " '两袖清风 ',\n",
       " '动听 ',\n",
       " '随遇而安 ',\n",
       " '金壁辉煌 ',\n",
       " '招笑儿 ',\n",
       " '水灵 ',\n",
       " '干脆 ',\n",
       " '含义明确 ',\n",
       " '微言大义 ',\n",
       " '斯斯文文 ',\n",
       " '爽直 ',\n",
       " '丰美 ',\n",
       " '友善 ',\n",
       " '亮闪闪 ',\n",
       " '俏皮 ',\n",
       " '网开一面 ',\n",
       " '端庄 ',\n",
       " '名誉 ',\n",
       " '时尚 ',\n",
       " '言简意赅 ',\n",
       " '端直 ',\n",
       " '应许 ',\n",
       " '原封不动 ',\n",
       " '耿耿 ',\n",
       " '鹄望 ',\n",
       " '水滴石穿 ',\n",
       " '扎扎实实 ',\n",
       " '执着 ',\n",
       " '打心眼里 ',\n",
       " '方方正正 ',\n",
       " '悄然 ',\n",
       " '精诚 ',\n",
       " '清口 ',\n",
       " '群威群胆 ',\n",
       " '端端正正 ',\n",
       " '合宜 ',\n",
       " '洒脱 ',\n",
       " '春风满面 ',\n",
       " '流芳后世 ',\n",
       " '松心 ',\n",
       " '守岁 ',\n",
       " '不耻下问 ',\n",
       " '跃跃欲试 ',\n",
       " '手勤 ',\n",
       " '精壮 ',\n",
       " '合掌 ',\n",
       " '无上光荣 ',\n",
       " '昂昂 ',\n",
       " '出众 ',\n",
       " '披肝沥胆 ',\n",
       " '隆 ',\n",
       " '守时 ',\n",
       " '身体结实 ',\n",
       " '知情达理 ',\n",
       " '斐然 ',\n",
       " '喷喷香 ',\n",
       " '给面子 ',\n",
       " '出色 ',\n",
       " '管用 ',\n",
       " '简易 ',\n",
       " '精神焕发 ',\n",
       " '溜光水滑 ',\n",
       " '不可缺少 ',\n",
       " '质朴 ',\n",
       " '企 ',\n",
       " '迎候 ',\n",
       " '匀 ',\n",
       " '婵娟 ',\n",
       " '做得好 ',\n",
       " '睿 ',\n",
       " '绚丽夺目 ',\n",
       " '铮铮 ',\n",
       " '不费吹灰之力 ',\n",
       " '轻车熟路 ',\n",
       " '匀称 ',\n",
       " '钟爱 ',\n",
       " '贵重 ',\n",
       " '保存良好 ',\n",
       " '有意 ',\n",
       " '入情入理 ',\n",
       " '朴 ',\n",
       " '不无小补 ',\n",
       " '够意思 ',\n",
       " '赏识 ',\n",
       " '容人 ',\n",
       " '婷婷袅袅 ',\n",
       " '见爱 ',\n",
       " '粗壮 ',\n",
       " '风度翩翩 ',\n",
       " '鲜亮 ',\n",
       " '思念 ',\n",
       " '合口味 ',\n",
       " '忠实 ',\n",
       " '高级 ',\n",
       " '有意义 ',\n",
       " '生花妙笔 ',\n",
       " '干干净净 ',\n",
       " '刻意 ',\n",
       " '矫捷 ',\n",
       " '利落 ',\n",
       " '舒畅 ',\n",
       " '尊崇 ',\n",
       " '一身是胆 ',\n",
       " '从头到底 ',\n",
       " '确实可靠 ',\n",
       " '平稳 ',\n",
       " '向往 ',\n",
       " '入画 ',\n",
       " '入时 ',\n",
       " '货真价实 ',\n",
       " '有两手 ',\n",
       " '慈悲为怀 ',\n",
       " '犒 ',\n",
       " '优等 ',\n",
       " '热 ',\n",
       " '逍遥 ',\n",
       " '多劳多得 ',\n",
       " '任意 ',\n",
       " '丕 ',\n",
       " '敦实 ',\n",
       " '正当 ',\n",
       " '滚瓜烂熟 ',\n",
       " '老练 ',\n",
       " '深湛 ',\n",
       " '有教益 ',\n",
       " '侧重 ',\n",
       " '高山仰止 ',\n",
       " '匀乎 ',\n",
       " '紧要 ',\n",
       " '热情洋溢 ',\n",
       " '看上 ',\n",
       " '宝 ',\n",
       " '怜爱 ',\n",
       " '可口 ',\n",
       " '全 ',\n",
       " '人欢马叫 ',\n",
       " '宏丽 ',\n",
       " '香喷喷 ',\n",
       " '国泰民安 ',\n",
       " '天姿国色 ',\n",
       " '刚劲有力 ',\n",
       " '深挚 ',\n",
       " '指望 ',\n",
       " '香醇 ',\n",
       " '馥馥 ',\n",
       " '风行 ',\n",
       " '喜乐 ',\n",
       " '不胜欣忭 ',\n",
       " '玲珑剔透 ',\n",
       " '靖 ',\n",
       " '把牢 ',\n",
       " '反哺 ',\n",
       " '匠心独具 ',\n",
       " '看上眼 ',\n",
       " '稳如泰山 ',\n",
       " '尊贵 ',\n",
       " '关键 ',\n",
       " '风流倜傥 ',\n",
       " '讲理 ',\n",
       " '五彩纷呈 ',\n",
       " '幽默滑稽 ',\n",
       " '空灵 ',\n",
       " '名副其实 ',\n",
       " '宜 ',\n",
       " '彬彬有礼 ',\n",
       " '称身 ',\n",
       " '唇红齿白 ',\n",
       " '胸怀坦白 ',\n",
       " '珍稀 ',\n",
       " '了然 ',\n",
       " '有滋味 ',\n",
       " '允准 ',\n",
       " '信得过 ',\n",
       " '正大光明 ',\n",
       " '有效 ',\n",
       " '逊 ',\n",
       " '一律 ',\n",
       " '清平 ',\n",
       " '红得发紫 ',\n",
       " '廉 ',\n",
       " '二话不说 ',\n",
       " '风平浪静 ',\n",
       " '果敢 ',\n",
       " '凝重 ',\n",
       " '玄妙 ',\n",
       " '状况良好 ',\n",
       " '善 ',\n",
       " '渊深 ',\n",
       " '老于世故 ',\n",
       " '安然无恙 ',\n",
       " '平等地 ',\n",
       " '眼光远大 ',\n",
       " '牢牢 ',\n",
       " '优越 ',\n",
       " '特许 ',\n",
       " '高精尖 ',\n",
       " '先人后己 ',\n",
       " '最新 ',\n",
       " '雄伟 ',\n",
       " '气度不凡 ',\n",
       " '笔直 ',\n",
       " '媢 ',\n",
       " '详密 ',\n",
       " '陶醉 ',\n",
       " '通顺 ',\n",
       " '言语流利 ',\n",
       " '过细 ',\n",
       " '妒火中烧 ',\n",
       " '望眼欲穿 ',\n",
       " '默认 ',\n",
       " '柔曼 ',\n",
       " '无容置疑 ',\n",
       " '有眉目 ',\n",
       " '一叶知秋 ',\n",
       " '热点 ',\n",
       " '平心静气 ',\n",
       " '千姿百态 ',\n",
       " '有一手 ',\n",
       " '因地制宜 ',\n",
       " '晟 ',\n",
       " '爱惜 ',\n",
       " '溢美 ',\n",
       " '森森 ',\n",
       " '妩 ',\n",
       " '爱宠 ',\n",
       " '新奇 ',\n",
       " '忠贞不屈 ',\n",
       " '浓艳 ',\n",
       " '豪爽 ',\n",
       " '体系化 ',\n",
       " '容易 ',\n",
       " '千恩万谢 ',\n",
       " '瓦亮 ',\n",
       " '翕 ',\n",
       " '义 ',\n",
       " '恋爱 ',\n",
       " '足智多谋 ',\n",
       " '百听不厌 ',\n",
       " '遂意 ',\n",
       " '谦逊 ',\n",
       " '革命 ',\n",
       " '雅致 ',\n",
       " '肯干 ',\n",
       " '无可争议 ',\n",
       " '通明透亮 ',\n",
       " '牢固 ',\n",
       " '照章 ',\n",
       " '乐乐呵呵 ',\n",
       " '企盼 ',\n",
       " '堂堂正正 ',\n",
       " '机警 ',\n",
       " '喜兴 ',\n",
       " '高效 ',\n",
       " '经常性 ',\n",
       " '聪慧 ',\n",
       " '纲领性 ',\n",
       " '光亮 ',\n",
       " '糖味 ',\n",
       " '卓越 ',\n",
       " '着眼于 ',\n",
       " '瞩望 ',\n",
       " '恭敬 ',\n",
       " '和软 ',\n",
       " '有求必应 ',\n",
       " '多情善感 ',\n",
       " '信赏必罚 ',\n",
       " '滴水穿石 ',\n",
       " '和蔼可亲 ',\n",
       " '膜拜 ',\n",
       " '目无全牛 ',\n",
       " '功德无量 ',\n",
       " '娟娟 ',\n",
       " '目光如炬 ',\n",
       " '大大方方 ',\n",
       " '稳扎稳打 ',\n",
       " '匪夷所思 ',\n",
       " '唱喏 ',\n",
       " '堕入爱河 ',\n",
       " '端平 ',\n",
       " '很快',\n",
       " '心软 ',\n",
       " '奇货可居 ',\n",
       " '舒适 ',\n",
       " '好受 ',\n",
       " '引人注意 ',\n",
       " '宽厚 ',\n",
       " '怏然自足 ',\n",
       " '纯厚 ',\n",
       " '厮熟 ',\n",
       " '聪明伶俐 ',\n",
       " '清洁卫生 ',\n",
       " '冒尖 ',\n",
       " '劬 ',\n",
       " '富丽堂皇 ',\n",
       " '和善 ',\n",
       " '变通 ',\n",
       " '绮 ',\n",
       " '值钱 ',\n",
       " '有朝气 ',\n",
       " '友爱 ',\n",
       " '细心 ',\n",
       " '祝福 ',\n",
       " '灼灼 ',\n",
       " '聪敏 ',\n",
       " '褒奖 ',\n",
       " '鬼迷心窍 ',\n",
       " '有门儿 ',\n",
       " '百废俱兴 ',\n",
       " '好生生 ',\n",
       " '正面 ',\n",
       " '敏锐 ',\n",
       " '撑台面 ',\n",
       " '利口 ',\n",
       " '甘醇 ',\n",
       " '专一 ',\n",
       " '有益 ',\n",
       " '佳 ',\n",
       " '光明磊落 ',\n",
       " '飞快 ',\n",
       " '劭 ',\n",
       " '哀婉 ',\n",
       " '投缘 ',\n",
       " '相当重要 ',\n",
       " '高高手儿 ',\n",
       " '卓然 ',\n",
       " '古朴 ',\n",
       " '和 ',\n",
       " '精良 ',\n",
       " '洌 ',\n",
       " '免票 ',\n",
       " '尽孝 ',\n",
       " '高山流水 ',\n",
       " '疼 ',\n",
       " '熟识 ',\n",
       " '忠贞不渝 ',\n",
       " '没的说 ',\n",
       " '至尊至贵 ',\n",
       " '坦直 ',\n",
       " '不屈 ',\n",
       " '味道好 ',\n",
       " '了当 ',\n",
       " '尽心竭力 ',\n",
       " '有名 ',\n",
       " '嘉奖 ',\n",
       " '有方 ',\n",
       " '懂礼 ',\n",
       " '睦 ',\n",
       " '打眼 ',\n",
       " '可歌可泣 ',\n",
       " '醊 ',\n",
       " '可靠 ',\n",
       " '祭拜 ',\n",
       " '灿烂 ',\n",
       " '各得其所 ',\n",
       " '正当年 ',\n",
       " '直来直去 ',\n",
       " '明摆着 ',\n",
       " '谢谢 ',\n",
       " '工工整整 ',\n",
       " '逸乐 ',\n",
       " '锦簇花团 ',\n",
       " '其实 ',\n",
       " '十全 ',\n",
       " '奖 ',\n",
       " '没弄脏 ',\n",
       " '数得着 ',\n",
       " '菁 ',\n",
       " '显明 ',\n",
       " '深沉 ',\n",
       " '明窗净几 ',\n",
       " '灯火辉煌 ',\n",
       " '妥 ',\n",
       " '实打实 ',\n",
       " '毫厘不差 ',\n",
       " '有文章 ',\n",
       " '恨不能 ',\n",
       " '欣赏 ',\n",
       " '刚好 ',\n",
       " '至关重大 ',\n",
       " '舒松 ',\n",
       " '祝颂 ',\n",
       " '拔尖 ',\n",
       " '叹服 ',\n",
       " '称誉 ',\n",
       " '恒定 ',\n",
       " '浅近 ',\n",
       " '膀阔腰圆 ',\n",
       " '朴拙 ',\n",
       " '嫣 ',\n",
       " '合理 ',\n",
       " '动态平衡 ',\n",
       " '健康美 ',\n",
       " '超卓 ',\n",
       " '浑俗和光 ',\n",
       " '有血气 ',\n",
       " '醉心 ',\n",
       " '吉祥 ',\n",
       " '荦荦大者 ',\n",
       " '顶天立地 ',\n",
       " '忠义 ',\n",
       " '祭扫 ',\n",
       " '有名气 ',\n",
       " '思 ',\n",
       " '醇和 ',\n",
       " '戆直 ',\n",
       " '用心良苦 ',\n",
       " '富甲一方 ',\n",
       " '显目 ',\n",
       " '郁郁苍苍 ',\n",
       " '喜不自胜 ',\n",
       " '老老实实 ',\n",
       " '手软 ',\n",
       " '光闪闪 ',\n",
       " '虎虎生气 ',\n",
       " '耳熟 ',\n",
       " '烁亮 ',\n",
       " '磅礴 ',\n",
       " '入木三分 ',\n",
       " '红红火火 ',\n",
       " '噱头 ',\n",
       " '细腻 ',\n",
       " '匀净 ',\n",
       " '行礼 ',\n",
       " '相当 ',\n",
       " '泠然 ',\n",
       " '俅 ',\n",
       " '俭朴 ',\n",
       " '心肠软 ',\n",
       " '水乳交融 ',\n",
       " '清新淡雅 ',\n",
       " '妖冶 ',\n",
       " '机动 ',\n",
       " '金玉 ',\n",
       " '眼尖 ',\n",
       " '团结 ',\n",
       " '音调优美 ',\n",
       " '头等 ',\n",
       " '小面额 ',\n",
       " '叫好 ',\n",
       " '承 ',\n",
       " '惟命是听 ',\n",
       " '十足 ',\n",
       " '少不了 ',\n",
       " '畅快 ',\n",
       " '有恒 ',\n",
       " '绰约多姿 ',\n",
       " '锦 ',\n",
       " '可信 ',\n",
       " '堂堂 ',\n",
       " '得意忘形 ',\n",
       " '踏踏实实 ',\n",
       " '心明眼亮 ',\n",
       " '倾心 ',\n",
       " '朴实 ',\n",
       " '特异 ',\n",
       " '把稳 ',\n",
       " '茏 ',\n",
       " '妩媚 ',\n",
       " '杲杲 ',\n",
       " '看中 ',\n",
       " '阗 ',\n",
       " '崇仰 ',\n",
       " '和易 ',\n",
       " '素朴 ',\n",
       " '红色 ',\n",
       " '大度 ',\n",
       " '有为 ',\n",
       " '跪拜 ',\n",
       " '适当 ',\n",
       " '一语双关 ',\n",
       " '赞许 ',\n",
       " '豪放 ',\n",
       " '排列整齐 ',\n",
       " '热心肠 ',\n",
       " '炽盛 ',\n",
       " '喜洋洋 ',\n",
       " '倾情 ',\n",
       " '和睦 ',\n",
       " '前程万里 ',\n",
       " '情意恳挚 ',\n",
       " '参谒 ',\n",
       " '地地道道 ',\n",
       " '倾国倾城 ',\n",
       " '深透 ',\n",
       " '敬慕 ',\n",
       " '重点 ',\n",
       " '晰 ',\n",
       " '昭著 ',\n",
       " '扎眼 ',\n",
       " '轻悠悠 ',\n",
       " '俱佳 ',\n",
       " '举止端庄 ',\n",
       " '欢乐 ',\n",
       " '蓬蓬勃勃 ',\n",
       " '秀媚 ',\n",
       " '颖 ',\n",
       " '嗓子好 ',\n",
       " '欢欢喜喜 ',\n",
       " '引人入胜 ',\n",
       " '支柱性 ',\n",
       " '驯顺 ',\n",
       " '嶷 ',\n",
       " '高深莫测 ',\n",
       " '醒豁 ',\n",
       " '佩服 ',\n",
       " '顺 ',\n",
       " '谦虚谨慎 ',\n",
       " '夤 ',\n",
       " '彪悍 ',\n",
       " '看在 ',\n",
       " '悄声 ',\n",
       " '讴歌 ',\n",
       " '形象地 ',\n",
       " '恬静 ',\n",
       " '一往情深 ',\n",
       " '出手不凡 ',\n",
       " '俨然 ',\n",
       " '眷恋 ',\n",
       " '和和睦睦 ',\n",
       " '应下 ',\n",
       " '灵巧 ',\n",
       " '光可鉴人 ',\n",
       " '融和 ',\n",
       " '嘴紧 ',\n",
       " '守法 ',\n",
       " '欣幸 ',\n",
       " '戴 ',\n",
       " '安如泰山 ',\n",
       " '矫健 ',\n",
       " '准许 ',\n",
       " '俭省 ',\n",
       " '整整齐齐 ',\n",
       " '翕然 ',\n",
       " '应有 ',\n",
       " '好说话儿 ',\n",
       " '深入浅出 ',\n",
       " '钦 ',\n",
       " '平等互利 ',\n",
       " '高雅 ',\n",
       " '风光旖旎 ',\n",
       " '英勇 ',\n",
       " '茁壮 ',\n",
       " '忌妒 ',\n",
       " '悉心 ',\n",
       " '拥护 ',\n",
       " '傲然 ',\n",
       " '勃 ',\n",
       " '吸引人眼球 ',\n",
       " '不错 ',\n",
       " '阳 ',\n",
       " '清静 ',\n",
       " '宽 ',\n",
       " '出身名门 ',\n",
       " '不武断 ',\n",
       " '准予 ',\n",
       " '睎 ',\n",
       " '清楚 ',\n",
       " '均 ',\n",
       " '新鲜 ',\n",
       " '热心 ',\n",
       " '有案可稽 ',\n",
       " '神魂颠倒 ',\n",
       " '承望 ',\n",
       " '哲 ',\n",
       " '挺括 ',\n",
       " '滑溜溜 ',\n",
       " '俏丽 ',\n",
       " '敬贺 ',\n",
       " '亮丽 ',\n",
       " '流畅 ',\n",
       " '热切 ',\n",
       " '正经八百 ',\n",
       " ...]"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 去掉相同的词\n",
    "positive = list(positive - intersection)\n",
    "positive"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "4e624170-8671-4d2d-bead-9ccb041564ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['阴毒 ',\n",
       " '累牍连篇 ',\n",
       " '语无伦次 ',\n",
       " '心灰意懒 ',\n",
       " '凄切 ',\n",
       " '嫩 ',\n",
       " '背悔 ',\n",
       " '错误 ',\n",
       " '不择手段 ',\n",
       " '冗赘 ',\n",
       " '乌烟瘴气 ',\n",
       " '怪罪 ',\n",
       " '牛气 ',\n",
       " '失悔 ',\n",
       " '抠唆 ',\n",
       " '凄凉 ',\n",
       " '懊 ',\n",
       " '罪恶 ',\n",
       " '没有学问 ',\n",
       " '啰啰嗦嗦 ',\n",
       " '鸷悍 ',\n",
       " '不可救药 ',\n",
       " '挤挤插插 ',\n",
       " '痴痴 ',\n",
       " '薄 ',\n",
       " '无口才 ',\n",
       " '呆气 ',\n",
       " '愁闷 ',\n",
       " '赝 ',\n",
       " '震惊 ',\n",
       " '人头攒动 ',\n",
       " '娇嫩 ',\n",
       " '没有头脑 ',\n",
       " '娇贵 ',\n",
       " '不仁 ',\n",
       " '无涵养 ',\n",
       " '小里小气 ',\n",
       " '雪上加霜 ',\n",
       " '惶惶然 ',\n",
       " '憋气 ',\n",
       " '恨入骨髓 ',\n",
       " '寥寂 ',\n",
       " '多病 ',\n",
       " '险 ',\n",
       " '詈 ',\n",
       " '强横 ',\n",
       " '太烂',\n",
       " '怆怳 ',\n",
       " '吓人 ',\n",
       " '脾气坏 ',\n",
       " '骄气 ',\n",
       " '啼笑皆非 ',\n",
       " '急巴巴 ',\n",
       " '引咎 ',\n",
       " '迷迷茫茫 ',\n",
       " '乱真 ',\n",
       " '面带嗔色 ',\n",
       " '缩头缩脑 ',\n",
       " '无力 ',\n",
       " '酸臭 ',\n",
       " '诞 ',\n",
       " '躁 ',\n",
       " '瘫软 ',\n",
       " '烟雾弥漫 ',\n",
       " '庸俗 ',\n",
       " '圆滑 ',\n",
       " '残 ',\n",
       " '玩忽 ',\n",
       " '荒诞无稽 ',\n",
       " '危亡 ',\n",
       " '非分 ',\n",
       " '阴暗 ',\n",
       " '羞恶 ',\n",
       " '装腔 ',\n",
       " '指摘 ',\n",
       " '必修 ',\n",
       " '畏首畏尾 ',\n",
       " '凶横 ',\n",
       " '过分简单化 ',\n",
       " '焦急 ',\n",
       " '贪婪 ',\n",
       " '灰茫茫 ',\n",
       " '不对称 ',\n",
       " '愚蒙 ',\n",
       " '悔之不及 ',\n",
       " '枯槁 ',\n",
       " '惆 ',\n",
       " '食而不化 ',\n",
       " '怠惰 ',\n",
       " '急功近利 ',\n",
       " '赘 ',\n",
       " '缈 ',\n",
       " '苍凉 ',\n",
       " '荒废 ',\n",
       " '气忿忿 ',\n",
       " '毫无价值 ',\n",
       " '大动肝火 ',\n",
       " '臭名远扬 ',\n",
       " '恕 ',\n",
       " '郁郁寡欢 ',\n",
       " '枯 ',\n",
       " '义愤填膺 ',\n",
       " '没关系 ',\n",
       " '白白 ',\n",
       " '凄然 ',\n",
       " '畏葸 ',\n",
       " '封建 ',\n",
       " '蒙蒙 ',\n",
       " '枉费心机 ',\n",
       " '勃然大怒 ',\n",
       " '骑虎难下 ',\n",
       " '低等 ',\n",
       " '害 ',\n",
       " '引咎自责 ',\n",
       " '恟 ',\n",
       " '冷冷 ',\n",
       " '反 ',\n",
       " '不好意思 ',\n",
       " '痛恶 ',\n",
       " '掊击 ',\n",
       " '羡余 ',\n",
       " '不对茬儿 ',\n",
       " '背靠背 ',\n",
       " '腐恶 ',\n",
       " '肩摩毂击 ',\n",
       " '扭扭捏捏 ',\n",
       " '诧异 ',\n",
       " '没理 ',\n",
       " '黄色 ',\n",
       " '繁乱 ',\n",
       " '后悔 ',\n",
       " '漫无目的 ',\n",
       " '索然无味 ',\n",
       " '罪恶滔天 ',\n",
       " '心切 ',\n",
       " '心如刀割 ',\n",
       " '得鱼忘筌 ',\n",
       " '惊疑 ',\n",
       " '碜 ',\n",
       " '扼腕 ',\n",
       " '剌戾 ',\n",
       " '墨 ',\n",
       " '毛躁 ',\n",
       " '怀疑 ',\n",
       " '怅惘 ',\n",
       " '惶恐 ',\n",
       " '溜号 ',\n",
       " '蛮悍 ',\n",
       " '惊异 ',\n",
       " '短浅 ',\n",
       " '拖泥带水 ',\n",
       " '啬 ',\n",
       " '稗 ',\n",
       " '惊怖 ',\n",
       " '劳而无功 ',\n",
       " '奸险 ',\n",
       " '使人疲劳 ',\n",
       " '顽钝 ',\n",
       " '辛 ',\n",
       " '势利眼 ',\n",
       " '说不过去 ',\n",
       " '喧杂 ',\n",
       " '麻木不仁 ',\n",
       " '大失所望 ',\n",
       " '失礼 ',\n",
       " '愤愤然 ',\n",
       " '暗沉沉 ',\n",
       " '不精确 ',\n",
       " '冷血 ',\n",
       " '拥挤 ',\n",
       " '小气 ',\n",
       " '惊慌 ',\n",
       " '未列计划 ',\n",
       " '哀哀切切 ',\n",
       " '等闲视之 ',\n",
       " '隐秘 ',\n",
       " '顾忌 ',\n",
       " '悖谬 ',\n",
       " '不近人情 ',\n",
       " '呼幺喝六 ',\n",
       " '讆 ',\n",
       " '苦闷 ',\n",
       " '朝不保夕 ',\n",
       " '迂拙 ',\n",
       " '不满 ',\n",
       " '气盛 ',\n",
       " '徒劳 ',\n",
       " '傲岸 ',\n",
       " '油渍渍 ',\n",
       " '凿空 ',\n",
       " '惶悚 ',\n",
       " '忸忸怩怩 ',\n",
       " '愁 ',\n",
       " '牵念 ',\n",
       " '张口结舌 ',\n",
       " '单薄 ',\n",
       " '小瞧 ',\n",
       " '垃圾',\n",
       " '兔死狐悲 ',\n",
       " '半新不旧 ',\n",
       " '荒僻 ',\n",
       " '官僚主义 ',\n",
       " '刻舟求剑 ',\n",
       " '没味 ',\n",
       " '失宜 ',\n",
       " '瞪眼 ',\n",
       " '犹犹豫豫 ',\n",
       " '颠连 ',\n",
       " '孤立无援 ',\n",
       " '死气沉沉 ',\n",
       " '铁公鸡一毛不拔 ',\n",
       " '很烂',\n",
       " '凶 ',\n",
       " '昏聩 ',\n",
       " '恶劣',\n",
       " '清冷 ',\n",
       " '多有微词 ',\n",
       " '变化万千 ',\n",
       " '恤 ',\n",
       " '庸 ',\n",
       " '无光泽 ',\n",
       " '火烧火燎 ',\n",
       " '所谓 ',\n",
       " '厌恨 ',\n",
       " '悻悻然 ',\n",
       " '杀人如麻 ',\n",
       " '挂名 ',\n",
       " '狂 ',\n",
       " '铺张 ',\n",
       " '漫无边际 ',\n",
       " '跅弛 ',\n",
       " '品头论足 ',\n",
       " '废物 ',\n",
       " '零零碎碎 ',\n",
       " '灰色 ',\n",
       " '漏洞百出 ',\n",
       " '白衣苍狗 ',\n",
       " '恼火 ',\n",
       " '从心所欲 ',\n",
       " '惊人 ',\n",
       " '低智 ',\n",
       " '差可 ',\n",
       " '颓 ',\n",
       " '憋着一肚子气 ',\n",
       " '恶贯满盈 ',\n",
       " '强行 ',\n",
       " '昏乱 ',\n",
       " '茕茕孑立 ',\n",
       " '茫茫然 ',\n",
       " '孤寂 ',\n",
       " '不对 ',\n",
       " '不名一文 ',\n",
       " '笨 ',\n",
       " '窘迫 ',\n",
       " '漫骂 ',\n",
       " '生气 ',\n",
       " '不尽如人意 ',\n",
       " '睁一只眼闭一只眼 ',\n",
       " '腐朽没落 ',\n",
       " '丧心病狂 ',\n",
       " '零七八碎 ',\n",
       " '索然寡味 ',\n",
       " '幻 ',\n",
       " '不力 ',\n",
       " '诡 ',\n",
       " '怅然若失 ',\n",
       " '好烂',\n",
       " '离题 ',\n",
       " '睁一眼闭一眼 ',\n",
       " '繁缛 ',\n",
       " '禽兽不如 ',\n",
       " '不稳定 ',\n",
       " '偏颇 ',\n",
       " '踌躇 ',\n",
       " '够戗 ',\n",
       " '懒惰 ',\n",
       " '偏听偏信 ',\n",
       " '乌压压 ',\n",
       " '顽固 ',\n",
       " '瞧不起 ',\n",
       " '胡乱 ',\n",
       " '气短 ',\n",
       " '踟 ',\n",
       " '惶然不安 ',\n",
       " '落套 ',\n",
       " '詈骂 ',\n",
       " '红眼 ',\n",
       " '战兢兢 ',\n",
       " '抠门儿 ',\n",
       " '未老先衰 ',\n",
       " '炸 ',\n",
       " '死板 ',\n",
       " '神气活现 ',\n",
       " '挂一漏万 ',\n",
       " '不足挂齿 ',\n",
       " '形影相吊 ',\n",
       " '欺诈性 ',\n",
       " '火急火燎 ',\n",
       " '锱铢必较 ',\n",
       " '心毒 ',\n",
       " '流气 ',\n",
       " '苛察 ',\n",
       " '戆头戆脑 ',\n",
       " '不适宜 ',\n",
       " '厝火积薪 ',\n",
       " '瘆 ',\n",
       " '滞销 ',\n",
       " '不理智 ',\n",
       " '诟 ',\n",
       " '松散 ',\n",
       " '自负 ',\n",
       " '令人窒息 ',\n",
       " '灯红酒绿 ',\n",
       " '骂得狗血喷头 ',\n",
       " '心酸 ',\n",
       " '翻然悔悟 ',\n",
       " '乖僻 ',\n",
       " '自恃 ',\n",
       " '猥亵 ',\n",
       " '无视 ',\n",
       " '懒得 ',\n",
       " '心惊肉跳 ',\n",
       " '繁复 ',\n",
       " '哭丧着脸 ',\n",
       " '颟顸 ',\n",
       " '死心眼 ',\n",
       " '难闻 ',\n",
       " '低沉 ',\n",
       " '好慢',\n",
       " '恕宥 ',\n",
       " '可叹 ',\n",
       " '逾分 ',\n",
       " '枉然 ',\n",
       " '不清洁 ',\n",
       " '挑毛病 ',\n",
       " '幽晦 ',\n",
       " '猫哭老鼠 ',\n",
       " '不合宜 ',\n",
       " '兔死狗烹 ',\n",
       " '自相矛盾 ',\n",
       " '价格不菲 ',\n",
       " '捶胸顿足 ',\n",
       " '杂沓 ',\n",
       " '不友好 ',\n",
       " '腥 ',\n",
       " '厉声 ',\n",
       " '蹇 ',\n",
       " '偷偷 ',\n",
       " '不人道 ',\n",
       " '追悔莫及 ',\n",
       " '啷 ',\n",
       " '悲戚 ',\n",
       " '骇人听闻 ',\n",
       " '尖嘴薄舌 ',\n",
       " '过当 ',\n",
       " '卖不掉 ',\n",
       " '过河拆桥 ',\n",
       " '大而化之 ',\n",
       " '极度悲哀 ',\n",
       " '婆婆妈妈 ',\n",
       " '严苛 ',\n",
       " '不合时宜 ',\n",
       " '难人 ',\n",
       " '寡言 ',\n",
       " '错 ',\n",
       " '现行 ',\n",
       " '浮噪 ',\n",
       " '不一致 ',\n",
       " '一脸稚气 ',\n",
       " '喧噪 ',\n",
       " '倥 ',\n",
       " '无精打采 ',\n",
       " '怜 ',\n",
       " '缺心眼儿 ',\n",
       " '低劣 ',\n",
       " '拉不下脸来 ',\n",
       " '红脸 ',\n",
       " '纷乱 ',\n",
       " '凄迷 ',\n",
       " '千疮百孔 ',\n",
       " '犯难 ',\n",
       " '问心有愧 ',\n",
       " '憋拗 ',\n",
       " '白忙活儿 ',\n",
       " '潜 ',\n",
       " '凶悍 ',\n",
       " '不合法 ',\n",
       " '变化不定 ',\n",
       " '坑人',\n",
       " '急不可待 ',\n",
       " '保守 ',\n",
       " '荒淫 ',\n",
       " '揭不开锅 ',\n",
       " '坑洼不平 ',\n",
       " '轻狂 ',\n",
       " '浮光掠影 ',\n",
       " '假仁假义 ',\n",
       " '忸怩作态 ',\n",
       " '眼光短浅 ',\n",
       " '寡淡 ',\n",
       " '狠心 ',\n",
       " '阢 ',\n",
       " '鸡毛蒜皮 ',\n",
       " '一锅粥 ',\n",
       " '糊涂 ',\n",
       " '气势汹汹 ',\n",
       " '心惊胆战 ',\n",
       " '狗眼看人 ',\n",
       " '荡 ',\n",
       " '不打紧 ',\n",
       " '穷奢极侈 ',\n",
       " '不可一世 ',\n",
       " '酷烈 ',\n",
       " '杂草丛生 ',\n",
       " '怅怅 ',\n",
       " '臭名昭彰 ',\n",
       " '发狂 ',\n",
       " '荒淫无耻 ',\n",
       " '鼠胆 ',\n",
       " '低档 ',\n",
       " '魔怔 ',\n",
       " '不顾 ',\n",
       " '妖 ',\n",
       " '抱恨 ',\n",
       " '恚恨 ',\n",
       " '凶巴巴 ',\n",
       " '冥冥 ',\n",
       " '邪 ',\n",
       " '侉 ',\n",
       " '悱 ',\n",
       " '香艳 ',\n",
       " '不均匀 ',\n",
       " '拿腔拿调 ',\n",
       " '挑逗性 ',\n",
       " '万马齐喑 ',\n",
       " '回头 ',\n",
       " '歪 ',\n",
       " '苦恼 ',\n",
       " '不绝如缕 ',\n",
       " '执拗 ',\n",
       " '零碎 ',\n",
       " '四面楚歌 ',\n",
       " '挤 ',\n",
       " '凶狠 ',\n",
       " '亏心 ',\n",
       " '酸涩 ',\n",
       " '偏激 ',\n",
       " '遗憾 ',\n",
       " '猥琐 ',\n",
       " '怜悯 ',\n",
       " '有碍观瞻 ',\n",
       " '哓 ',\n",
       " '饶人 ',\n",
       " '焦心 ',\n",
       " '心狠 ',\n",
       " '辛辛苦苦 ',\n",
       " '轸 ',\n",
       " '无限制 ',\n",
       " '虚惊 ',\n",
       " '嗔 ',\n",
       " '不可降解 ',\n",
       " '犷悍 ',\n",
       " '诡计多端 ',\n",
       " '险诈 ',\n",
       " '老弱病残 ',\n",
       " '不足轻重 ',\n",
       " '见异思迁 ',\n",
       " '松垮垮 ',\n",
       " '哀愁 ',\n",
       " '低能 ',\n",
       " '怕生 ',\n",
       " '凛凛 ',\n",
       " '反常 ',\n",
       " '惊奇 ',\n",
       " '寒伧 ',\n",
       " '假 ',\n",
       " '不辨菽麦 ',\n",
       " '残毒 ',\n",
       " '无价值 ',\n",
       " '悭吝 ',\n",
       " '造次 ',\n",
       " '腐化 ',\n",
       " '不屑于 ',\n",
       " '浑浊 ',\n",
       " '不愿意 ',\n",
       " '芴 ',\n",
       " '干瘪瘪 ',\n",
       " '荒谬 ',\n",
       " '反叛 ',\n",
       " '异形 ',\n",
       " '荏弱 ',\n",
       " '腆 ',\n",
       " '可惊 ',\n",
       " '弱小 ',\n",
       " '恼恨 ',\n",
       " '刺耳 ',\n",
       " '竹篮打水 ',\n",
       " '淡然 ',\n",
       " '没劲 ',\n",
       " '偏斜 ',\n",
       " '忪 ',\n",
       " '误 ',\n",
       " '含含混混 ',\n",
       " '憋 ',\n",
       " '抱疚 ',\n",
       " '一仍旧贯 ',\n",
       " '憎 ',\n",
       " '奸猾 ',\n",
       " '笑骂 ',\n",
       " '窳劣 ',\n",
       " '如泣如诉 ',\n",
       " '讪讪 ',\n",
       " '苍白 ',\n",
       " '宥 ',\n",
       " '乖剌 ',\n",
       " '颓唐 ',\n",
       " '要不得 ',\n",
       " '骄人 ',\n",
       " '腐臭 ',\n",
       " '残破 ',\n",
       " '艰巨 ',\n",
       " '怒火冲天 ',\n",
       " '意马心猿 ',\n",
       " '不确切 ',\n",
       " '委罪 ',\n",
       " '性情急躁 ',\n",
       " '刁悍 ',\n",
       " '土 ',\n",
       " '陈旧 ',\n",
       " '恶劣 ',\n",
       " '天昏地暗 ',\n",
       " '灰蒙蒙 ',\n",
       " '渺然 ',\n",
       " '心如刀绞 ',\n",
       " '凌乱 ',\n",
       " '得寸进尺 ',\n",
       " '发怵 ',\n",
       " '呆愣愣 ',\n",
       " '豺狼当道 ',\n",
       " '不爱交际 ',\n",
       " '不济事 ',\n",
       " '不可告人 ',\n",
       " '胡 ',\n",
       " '唯我独尊 ',\n",
       " '厉害 ',\n",
       " '缺心眼 ',\n",
       " '比肩接踵 ',\n",
       " '缭乱 ',\n",
       " '有一搭没一搭 ',\n",
       " '朝三暮四 ',\n",
       " '鱼龙混杂 ',\n",
       " '够呛 ',\n",
       " '槁木死灰 ',\n",
       " '愠怒 ',\n",
       " '二手 ',\n",
       " '蓬首垢面 ',\n",
       " '堵 ',\n",
       " '惊怪 ',\n",
       " '失节 ',\n",
       " '悻然 ',\n",
       " '踌躇不决 ',\n",
       " '出手阔气 ',\n",
       " '千金一掷 ',\n",
       " '找茬儿 ',\n",
       " '动荡 ',\n",
       " '无情无义 ',\n",
       " '悔不当初 ',\n",
       " '皇皇 ',\n",
       " '不行 ',\n",
       " '无用 ',\n",
       " '繁重 ',\n",
       " '蓬头垢面 ',\n",
       " '令人遗憾 ',\n",
       " '凄怨 ',\n",
       " '假想 ',\n",
       " '嗲 ',\n",
       " '苛责 ',\n",
       " '自大 ',\n",
       " '不相适应 ',\n",
       " '自私 ',\n",
       " '灰秃秃 ',\n",
       " '正色 ',\n",
       " '平淡无味 ',\n",
       " '喝叱 ',\n",
       " '不合逻辑 ',\n",
       " '混浊 ',\n",
       " '烦忧 ',\n",
       " '呆滞 ',\n",
       " '粗心 ',\n",
       " '老掉牙 ',\n",
       " '绵软 ',\n",
       " '数不上 ',\n",
       " '低值 ',\n",
       " '残败 ',\n",
       " '惘 ',\n",
       " '没受过教育 ',\n",
       " '天南海北 ',\n",
       " '无原则 ',\n",
       " '斜歪 ',\n",
       " '左 ',\n",
       " '稀里糊涂 ',\n",
       " '吹胡子瞪眼 ',\n",
       " '虚设 ',\n",
       " '没礼貌 ',\n",
       " '淡淡 ',\n",
       " '不透气 ',\n",
       " '抑郁寡欢 ',\n",
       " '懈怠 ',\n",
       " '嚣杂 ',\n",
       " '羞人 ',\n",
       " '残损 ',\n",
       " '迷离倘恍 ',\n",
       " '浮滑 ',\n",
       " '机械式 ',\n",
       " '阴沉沉 ',\n",
       " '利令智昏 ',\n",
       " '脏乱 ',\n",
       " '太虚 ',\n",
       " '邋遢 ',\n",
       " '无所帮助 ',\n",
       " '肋脦 ',\n",
       " '来火 ',\n",
       " '罪孽深重 ',\n",
       " '动摇 ',\n",
       " '索然乏味 ',\n",
       " '不以为然 ',\n",
       " '不能解救 ',\n",
       " '批斗 ',\n",
       " '如鲠在喉 ',\n",
       " '晦暗 ',\n",
       " '狂躁 ',\n",
       " '赤贫 ',\n",
       " '死硬 ',\n",
       " '忡 ',\n",
       " '质次价高 ',\n",
       " '散漫 ',\n",
       " '鼎沸 ',\n",
       " '潦草 ',\n",
       " '模糊 ',\n",
       " '守株待兔 ',\n",
       " '矫揉造作 ',\n",
       " '繁冗 ',\n",
       " '无实效 ',\n",
       " '鄙弃 ',\n",
       " '崎岖不平 ',\n",
       " '丧志 ',\n",
       " '昏头昏脑 ',\n",
       " '变化多端 ',\n",
       " '下三滥 ',\n",
       " '大面额 ',\n",
       " '忧 ',\n",
       " '没什么了不起 ',\n",
       " '乌灯黑火 ',\n",
       " '不可逾越 ',\n",
       " '旧 ',\n",
       " '死死 ',\n",
       " '尖酸 ',\n",
       " '淫乱 ',\n",
       " '无动于衷 ',\n",
       " '担心 ',\n",
       " '倔犟 ',\n",
       " '黑心',\n",
       " '变脸 ',\n",
       " '废旧 ',\n",
       " '阴森 ',\n",
       " '猥贱 ',\n",
       " '耳热 ',\n",
       " '负气 ',\n",
       " '下乘 ',\n",
       " '寒酸 ',\n",
       " '暗自 ',\n",
       " '眼皮子高 ',\n",
       " '串秧儿 ',\n",
       " '迷蒙蒙 ',\n",
       " '游移 ',\n",
       " '不为人知 ',\n",
       " '莽 ',\n",
       " '凄酸 ',\n",
       " '阔气 ',\n",
       " '没头脑 ',\n",
       " '哈喇 ',\n",
       " '骂得狗血淋头 ',\n",
       " '责骂 ',\n",
       " '斗 ',\n",
       " '被动 ',\n",
       " '碍眼 ',\n",
       " '行为不检 ',\n",
       " '愚痴 ',\n",
       " '冰冷 ',\n",
       " '痛恨 ',\n",
       " '眷顾 ',\n",
       " '卑鄙 ',\n",
       " '板起脸 ',\n",
       " '麻麻黑 ',\n",
       " '叶公好龙 ',\n",
       " '昏 ',\n",
       " '真慢',\n",
       " '不重要 ',\n",
       " '苛刻 ',\n",
       " '暴戾 ',\n",
       " '敌对 ',\n",
       " '猜疑 ',\n",
       " '仇视 ',\n",
       " '头脑空虚 ',\n",
       " '哀痛 ',\n",
       " '动作迟顿 ',\n",
       " '懆懆 ',\n",
       " '喧 ',\n",
       " '气昂昂 ',\n",
       " '峭直 ',\n",
       " '慢',\n",
       " '什 ',\n",
       " '目中无人 ',\n",
       " '自咎 ',\n",
       " '离索 ',\n",
       " '度量小 ',\n",
       " '挂记 ',\n",
       " '申饬 ',\n",
       " '悖 ',\n",
       " '可有可无 ',\n",
       " '艰难曲折 ',\n",
       " '狼心狗肺 ',\n",
       " '臭 ',\n",
       " '哀怜 ',\n",
       " '小家子相 ',\n",
       " '零星 ',\n",
       " '糊里糊涂 ',\n",
       " '粗鲁 ',\n",
       " '斥骂 ',\n",
       " '刻板 ',\n",
       " '污 ',\n",
       " '心虚 ',\n",
       " '荒芜 ',\n",
       " '竹篮子打水 ',\n",
       " '颓然 ',\n",
       " '怜恤 ',\n",
       " '无赖 ',\n",
       " '慑 ',\n",
       " '晕头转向 ',\n",
       " '暗地里 ',\n",
       " '乱了营 ',\n",
       " '阴郁 ',\n",
       " '萧瑟 ',\n",
       " '绕脖子 ',\n",
       " '崎 ',\n",
       " '残虐 ',\n",
       " '人不知，鬼不觉 ',\n",
       " '抱歉 ',\n",
       " '出气 ',\n",
       " '嗔怒 ',\n",
       " '没骨头 ',\n",
       " '暮气 ',\n",
       " '一怔 ',\n",
       " '太慢',\n",
       " '波谲云诡 ',\n",
       " '畸形 ',\n",
       " '狎 ',\n",
       " '疑神疑鬼 ',\n",
       " '训戒 ',\n",
       " '忧愁 ',\n",
       " '掎 ',\n",
       " '蛇蝎心肠 ',\n",
       " '微贱 ',\n",
       " '可悲 ',\n",
       " '漠漠 ',\n",
       " '穷凶极恶 ',\n",
       " '凄厉 ',\n",
       " '腐烂 ',\n",
       " '油腻腻 ',\n",
       " '不巧 ',\n",
       " '一不小心 ',\n",
       " '气呼呼 ',\n",
       " '痛心疾首 ',\n",
       " '怆然 ',\n",
       " '傻 ',\n",
       " '易怒 ',\n",
       " '不友善 ',\n",
       " '凶险 ',\n",
       " '风雨飘摇 ',\n",
       " '渺渺 ',\n",
       " '哩溜歪斜 ',\n",
       " '肃 ',\n",
       " '半信半疑 ',\n",
       " '蹈常袭故 ',\n",
       " '苶 ',\n",
       " '荒乱 ',\n",
       " '烦难 ',\n",
       " '绷 ',\n",
       " '乖张 ',\n",
       " '不当 ',\n",
       " '胆小如鼠 ',\n",
       " '贫困 ',\n",
       " '悲切切 ',\n",
       " '土俗 ',\n",
       " '背后 ',\n",
       " '介怀 ',\n",
       " '啧有烦言 ',\n",
       " '不是滋味 ',\n",
       " '忧惧 ',\n",
       " '评头论足 ',\n",
       " '愤愤不平 ',\n",
       " '硗 ',\n",
       " '令人恼火 ',\n",
       " '不堪造就 ',\n",
       " '嫌厌 ',\n",
       " '过气 ',\n",
       " '无心 ',\n",
       " '虚无 ',\n",
       " '狡兔三窟 ',\n",
       " '歧视 ',\n",
       " '伤怀 ',\n",
       " '忸怩 ',\n",
       " '低效 ',\n",
       " '派不是 ',\n",
       " '咒诅 ',\n",
       " '夹七夹八 ',\n",
       " '暴烈 ',\n",
       " '不屑一顾 ',\n",
       " '愠 ',\n",
       " '死心塌地 ',\n",
       " '阽 ',\n",
       " '不现实 ',\n",
       " '面无人色 ',\n",
       " '内疚 ',\n",
       " '臭骂 ',\n",
       " '动怒 ',\n",
       " '学究气 ',\n",
       " '愤怒 ',\n",
       " '溢价 ',\n",
       " '人身攻击 ',\n",
       " '娇痴 ',\n",
       " '持异议 ',\n",
       " '倔 ',\n",
       " '怒不可遏 ',\n",
       " '示不同意 ',\n",
       " '悯 ',\n",
       " '嫌弃 ',\n",
       " '荒诞派 ',\n",
       " '穷极潦倒 ',\n",
       " '涵容 ',\n",
       " '生硬 ',\n",
       " '名誉扫地 ',\n",
       " '无补于事 ',\n",
       " '义正词严 ',\n",
       " '轻佻 ',\n",
       " '封闭 ',\n",
       " '忧悒 ',\n",
       " '詟 ',\n",
       " '烈性子 ',\n",
       " '扬长 ',\n",
       " '垂怜 ',\n",
       " '含怨 ',\n",
       " '皱皱巴巴 ',\n",
       " '板着面孔 ',\n",
       " '拮据 ',\n",
       " '病态 ',\n",
       " '未便 ',\n",
       " '放荡不羁 ',\n",
       " '悲观 ',\n",
       " '猴 ',\n",
       " '找岔子 ',\n",
       " '黑灯瞎火 ',\n",
       " '焦炙 ',\n",
       " '难受 ',\n",
       " '凄冷 ',\n",
       " '多虑 ',\n",
       " '没见过世面 ',\n",
       " '闭塞 ',\n",
       " '哀怨 ',\n",
       " '盲目 ',\n",
       " '泛 ',\n",
       " '骈枝 ',\n",
       " '心里堵得慌 ',\n",
       " '不可逆转 ',\n",
       " '区区 ',\n",
       " '哀矜 ',\n",
       " '马马虎虎 ',\n",
       " '乏 ',\n",
       " '难 ',\n",
       " '繁难 ',\n",
       " '繁芜 ',\n",
       " '叫苦连天 ',\n",
       " '哀切 ',\n",
       " '瘠 ',\n",
       " '悒郁 ',\n",
       " '依稀 ',\n",
       " '漫无目标 ',\n",
       " '糟心 ',\n",
       " '私底下 ',\n",
       " '嗔怪 ',\n",
       " '怄 ',\n",
       " '烦琐 ',\n",
       " '严 ',\n",
       " '难上加难 ',\n",
       " '摇摇欲坠 ',\n",
       " '大大咧咧 ',\n",
       " '无语',\n",
       " '得饶人处且饶人 ',\n",
       " '晦冥 ',\n",
       " '懊恨 ',\n",
       " '德性 ',\n",
       " '口是心非 ',\n",
       " '娄 ',\n",
       " '神志委靡 ',\n",
       " '子虚乌有 ',\n",
       " '骇异 ',\n",
       " '百无聊赖 ',\n",
       " '匿名 ',\n",
       " '恼 ',\n",
       " '沉滞 ',\n",
       " '花搭着 ',\n",
       " '愣怔怔 ',\n",
       " '反社会 ',\n",
       " '老大难 ',\n",
       " '视同儿戏 ',\n",
       " '不兴 ',\n",
       " '零乱 ',\n",
       " '铁血 ',\n",
       " '鄙视 ',\n",
       " '焦虑 ',\n",
       " '失望 ',\n",
       " '气哼哼 ',\n",
       " '狰狞 ',\n",
       " '破口大骂 ',\n",
       " '平淡无奇 ',\n",
       " '非 ',\n",
       " '萧然 ',\n",
       " '心烦意乱 ',\n",
       " '可怕 ',\n",
       " '皮相 ',\n",
       " '极差',\n",
       " '懒到极点 ',\n",
       " '弱势 ',\n",
       " '赤地千里 ',\n",
       " '稀松 ',\n",
       " '不管三七二十一 ',\n",
       " '悛 ',\n",
       " '渺小 ',\n",
       " '胆怯 ',\n",
       " '窘促 ',\n",
       " '黑乎乎 ',\n",
       " '叫骂 ',\n",
       " '迟疑不决 ',\n",
       " '含悲 ',\n",
       " '空虚 ',\n",
       " '娇羞 ',\n",
       " '黯然神伤 ',\n",
       " '拘礼 ',\n",
       " '恶心 ',\n",
       " '杌 ',\n",
       " '别别扭扭 ',\n",
       " '冒有风险 ',\n",
       " '凄 ',\n",
       " '愚钝 ',\n",
       " '策略 ',\n",
       " '朦朦胧胧 ',\n",
       " '微愠 ',\n",
       " '狙 ',\n",
       " '非正常 ',\n",
       " '虚诞 ',\n",
       " '申讨 ',\n",
       " '碌碌无为 ',\n",
       " '牛 ',\n",
       " '蓬散 ',\n",
       " '气头上 ',\n",
       " '骇惧 ',\n",
       " '不肖 ',\n",
       " '机械 ',\n",
       " '脸皮薄 ',\n",
       " '无眉目 ',\n",
       " '囊空如洗 ',\n",
       " '肉麻 ',\n",
       " '阴性 ',\n",
       " '荒 ',\n",
       " '弱 ',\n",
       " '讥嘲 ',\n",
       " '大海捞针 ',\n",
       " '好差',\n",
       " '俚俗 ',\n",
       " '毛糙 ',\n",
       " '祸从天降 ',\n",
       " '暴跳 ',\n",
       " '装样子 ',\n",
       " '悚然 ',\n",
       " '滞钝 ',\n",
       " '数说 ',\n",
       " '豪侈 ',\n",
       " '哀痛欲绝 ',\n",
       " '胆颤心惊 ',\n",
       " '退化 ',\n",
       " '世俗 ',\n",
       " '无生气 ',\n",
       " '干干巴巴 ',\n",
       " '莽苍 ',\n",
       " '诅骂 ',\n",
       " '训斥 ',\n",
       " '犯怵 ',\n",
       " '好容易 ',\n",
       " '装备不良 ',\n",
       " '惨无人道 ',\n",
       " ...]"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "negative = list(negative - intersection)\n",
    "negative"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "d1b1cc9d-9bfd-45bb-9466-9d1d48ef35f4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "       word  weight\n",
       "0       倜傥        1\n",
       "1     人寿年丰        1\n",
       "2        惺        1\n",
       "3       锃亮        1\n",
       "4     非常热心        1\n",
       "...     ...     ...\n",
       "4435  别有风味        1\n",
       "4436    爱好        1\n",
       "4437  有嘴无心        1\n",
       "4438     稳        1\n",
       "4439    太棒了       1\n",
       "\n",
       "[4440 rows x 2 columns]"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "# 正面词语赋予初始权重1，负面词语赋予初始权重-1\n",
    "positive = pd.DataFrame({\"word\": positive, \"weight\": [1] * len(positive)})\n",
    "positive"
   ]
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  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "c827ca52-cea6-4bac-845a-ded3cf180744",
   "metadata": {},
   "outputs": [
    {
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       "       word  weight\n",
       "0       阴毒       -1\n",
       "1     累牍连篇       -1\n",
       "2     语无伦次       -1\n",
       "3     心灰意懒       -1\n",
       "4       凄切       -1\n",
       "...     ...     ...\n",
       "4237    做作       -1\n",
       "4238    任纵       -1\n",
       "4239    含愤       -1\n",
       "4240  满不在乎       -1\n",
       "4241   不好客       -1\n",
       "\n",
       "[4242 rows x 2 columns]"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "negative = pd.DataFrame({\"word\": negative, \"weight\": [-1] * len(negative)})\n",
    "negative"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "b0b686ff-7ed2-4b00-a747-5fc2e31077a5",
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   "outputs": [
    {
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       "<p>8682 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       word  weight\n",
       "0       倜傥        1\n",
       "1     人寿年丰        1\n",
       "2        惺        1\n",
       "3       锃亮        1\n",
       "4     非常热心        1\n",
       "...     ...     ...\n",
       "8677    做作       -1\n",
       "8678    任纵       -1\n",
       "8679    含愤       -1\n",
       "8680  满不在乎       -1\n",
       "8681   不好客       -1\n",
       "\n",
       "[8682 rows x 2 columns]"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 将分词结果与正负面情感词表合并，定位情感词\n",
    "posneg = pd.concat([positive, negative], ignore_index=True)\n",
    "posneg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "37ba0919-dc63-4987-a068-065df9d8eeed",
   "metadata": {},
   "outputs": [
    {
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       "      <td>天</td>\n",
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       "      <td>NaN</td>\n",
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       "      <th>24756</th>\n",
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       "      <td>没人</td>\n",
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       "      <td>NaN</td>\n",
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       "      <th>24757</th>\n",
       "      <td>neg</td>\n",
       "      <td>1999</td>\n",
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       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>24758</th>\n",
       "      <td>neg</td>\n",
       "      <td>1999</td>\n",
       "      <td>d</td>\n",
       "      <td>太</td>\n",
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       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>24759</th>\n",
       "      <td>neg</td>\n",
       "      <td>1999</td>\n",
       "      <td>a</td>\n",
       "      <td>差</td>\n",
       "      <td>9</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>24760 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      content_type  index_content nature word  index_word  weight\n",
       "0              pos              1     ns   东西           0     NaN\n",
       "1              pos              1      v   收到           1     NaN\n",
       "2              pos              1      r  这么久           2     NaN\n",
       "3              pos              1      v    忘           3     NaN\n",
       "4              pos              1      v   好评           4     1.0\n",
       "...            ...            ...    ...  ...         ...     ...\n",
       "24755          neg           1999      q    天           5     NaN\n",
       "24756          neg           1999      v   没人           6     NaN\n",
       "24757          neg           1999      n   售后           7     NaN\n",
       "24758          neg           1999      d    太           8     NaN\n",
       "24759          neg           1999      a    差           9     NaN\n",
       "\n",
       "[24760 rows x 6 columns]"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_posneg = pd.merge(left=word, right=posneg, on='word', how='left')\n",
    "data_posneg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "36ff8555-e60b-474f-ac63-419d3bd4262f",
   "metadata": {},
   "outputs": [
    {
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       "      <td>r</td>\n",
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       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
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       "      <th>3</th>\n",
       "      <td>pos</td>\n",
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       "      <td>忘</td>\n",
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       "      <td>NaN</td>\n",
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       "      <th>4</th>\n",
       "      <td>pos</td>\n",
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       "      <td>好评</td>\n",
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       "      <th>24755</th>\n",
       "      <td>neg</td>\n",
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       "      <td>NaN</td>\n",
       "    </tr>\n",
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       "      <td>neg</td>\n",
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       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24758</th>\n",
       "      <td>neg</td>\n",
       "      <td>1999</td>\n",
       "      <td>d</td>\n",
       "      <td>太</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24759</th>\n",
       "      <td>neg</td>\n",
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       "      <td>a</td>\n",
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       "      <td>9</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>24760 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      content_type  index_content nature word  index_word  weight\n",
       "0              pos              1     ns   东西           0     NaN\n",
       "1              pos              1      v   收到           1     NaN\n",
       "2              pos              1      r  这么久           2     NaN\n",
       "3              pos              1      v    忘           3     NaN\n",
       "4              pos              1      v   好评           4     1.0\n",
       "...            ...            ...    ...  ...         ...     ...\n",
       "24755          neg           1999      q    天           5     NaN\n",
       "24756          neg           1999      v   没人           6     NaN\n",
       "24757          neg           1999      n   售后           7     NaN\n",
       "24758          neg           1999      d    太           8     NaN\n",
       "24759          neg           1999      a    差           9     NaN\n",
       "\n",
       "[24760 rows x 6 columns]"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 先按评论id排序，再按在评论中的位置排序\n",
    "data_posneg = data_posneg.sort_values(by=['index_content', 'index_word'])\n",
    "data_posneg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "b93a0f08-afa2-4312-9c67-0f1e03db6354",
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "     content_type  index_content nature word  index_word  weight  \\\n",
       "0             pos              1      v   好评           4     1.0   \n",
       "1             pos              1      v   值得           6     1.0   \n",
       "2             pos              1      n   信赖           7     1.0   \n",
       "3             pos              1      v   值得          12     1.0   \n",
       "4             pos              2      v   感谢           3     1.0   \n",
       "...           ...            ...    ...  ...         ...     ...   \n",
       "1454          neg           1988      a    贵           7    -1.0   \n",
       "1455          neg           1994      a    高           3    -1.0   \n",
       "1456          neg           1997      n   差评          15    -1.0   \n",
       "1457          neg           1998     nz   漏电           2    -1.0   \n",
       "1458          neg           1999      v   挺快           2     1.0   \n",
       "\n",
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       "4              1.0     17  \n",
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       "1456          -1.0  24742  \n",
       "1457          -1.0  24749  \n",
       "1458           1.0  24752  \n",
       "\n",
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     "execution_count": 98,
     "metadata": {},
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   ],
   "source": [
    "# 根据情感词前面两个位置的词语是否存在否定词或双层否定词对情感值进行修正\n",
    "# 载入否定词表\n",
    "notdict = pd.read_csv(\"D:/Users/19202/Desktop/not.csv\")\n",
    "# 处理否定修饰词\n",
    "# 构造新列，作为经过否定词修正后的情感值\n",
    "data_posneg['amend_weight'] = data_posneg['weight'] \n",
    "data_posneg['id'] = np.arange(0, len(data_posneg))\n",
    "# 只保留有情感值的词语\n",
    "only_inclination = data_posneg.dropna()  \n",
    "# 修改索引\n",
    "only_inclination.index = np.arange(0, len(only_inclination))\n",
    "only_inclination "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "cdee14e7-2d3d-46fc-afde-ce67b1aa4f3a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "# 获取情感词的索引\n",
    "index = only_inclination['id']\n",
    "\n",
    "# 遍历每个情感词\n",
    "for i in np.arange(0, len(only_inclination)):\n",
    "    # 提取第i个情感词所在的评论\n",
    "    review = data_posneg[data_posneg['index_content'] == only_inclination['index_content'][i]]\n",
    "    # 修改索引，使其从0开始\n",
    "    review.index = np.arange(0, len(review))\n",
    "    # 获取第i个情感词在文档中的位置\n",
    "    affective = only_inclination['index_word'][i]\n",
    "\n",
    "    if affective == 1:\n",
    "        # 检查情感词前面的单词是否在否定词表中\n",
    "        ne = sum([i in notdict['term'] for i in review['word'][affective - 1]])\n",
    "        if ne == 1:\n",
    "            # 如果存在否定词，调整情感词的权重为相反数\n",
    "            data_posneg['amend_weight'][index[i]] = -data_posneg['weight'][index[i]]\n",
    "    elif affective > 1:\n",
    "        # 检查情感词前面两个位置的词语是否在否定词表中\n",
    "        ne = sum([i in notdict['term'] for i in review['word'][affective - 1:affective - 2]])\n",
    "        if ne == 1:\n",
    "            # 如果存在一个否定词，调整情感词的权重为相反数\n",
    "            data_posneg['amend_weight'][index[i]] = -data_posneg['weight'][index[i]]"
   ]
  },
  {
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   "execution_count": 100,
   "id": "e2f7954a-8b9c-46f2-a1fd-901aa82e2969",
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      "text/plain": [
       "     content_type  index_content nature word  index_word  weight  \\\n",
       "0             pos              1      v   好评           4     1.0   \n",
       "1             pos              1      v   值得           6     1.0   \n",
       "2             pos              1      n   信赖           7     1.0   \n",
       "3             pos              1      v   值得          12     1.0   \n",
       "4             pos              2      v   感谢           3     1.0   \n",
       "...           ...            ...    ...  ...         ...     ...   \n",
       "1454          neg           1988      a    贵           7    -1.0   \n",
       "1455          neg           1994      a    高           3    -1.0   \n",
       "1456          neg           1997      n   差评          15    -1.0   \n",
       "1457          neg           1998     nz   漏电           2    -1.0   \n",
       "1458          neg           1999      v   挺快           2     1.0   \n",
       "\n",
       "      amend_weight     id  \n",
       "0              1.0      4  \n",
       "1              1.0      6  \n",
       "2              1.0      7  \n",
       "3              1.0     12  \n",
       "4              1.0     17  \n",
       "...            ...    ...  \n",
       "1454          -1.0  24644  \n",
       "1455          -1.0  24714  \n",
       "1456          -1.0  24742  \n",
       "1457          -1.0  24749  \n",
       "1458           1.0  24752  \n",
       "\n",
       "[1459 rows x 8 columns]"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "only_inclination"
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  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "89120b86-adf7-49ba-a325-e78a3d47ec9b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "0           4\n",
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       "3          12\n",
       "4          17\n",
       "        ...  \n",
       "1454    24644\n",
       "1455    24714\n",
       "1456    24742\n",
       "1457    24749\n",
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       "Name: id, Length: 1459, dtype: int32"
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     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "index"
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  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "f4721394-5758-429a-9217-063eb69d5e7c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "     index_content  amend_weight\n",
       "0                1           4.0\n",
       "1                2           1.0\n",
       "2                4           4.0\n",
       "3                5           1.0\n",
       "4                6           1.0\n",
       "..             ...           ...\n",
       "896           1988          -1.0\n",
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       "\n",
       "[901 rows x 2 columns]"
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     },
     "execution_count": 102,
     "metadata": {},
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   ],
   "source": [
    "# 计算每条评论的情感值\n",
    "emotional_value = only_inclination.groupby(['index_content'], as_index=False)['amend_weight'].sum()\n",
    "\n",
    "# 去除情感值为0的评论\n",
    "emotional_value = emotional_value[emotional_value['amend_weight'] != 0]\n",
    "\n",
    "# 重置索引，丢弃旧索引，并在原地修改\n",
    "emotional_value.reset_index(drop=True, inplace=True)\n",
    "\n",
    "# 输出情感值数据框\n",
    "emotional_value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "376f2784-94af-483c-ad27-ffda5d892f27",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\19202\\AppData\\Local\\Temp\\ipykernel_3540\\2521707949.py:3: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0!\n",
      "You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy.\n",
      "A typical example is when you are setting values in a column of a DataFrame, like:\n",
      "\n",
      "df[\"col\"][row_indexer] = value\n",
      "\n",
      "Use `df.loc[row_indexer, \"col\"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`.\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "  emotional_value['a_type'][emotional_value['amend_weight'] > 0] = 'pos'\n",
      "C:\\Users\\19202\\AppData\\Local\\Temp\\ipykernel_3540\\2521707949.py:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  emotional_value['a_type'][emotional_value['amend_weight'] > 0] = 'pos'\n",
      "C:\\Users\\19202\\AppData\\Local\\Temp\\ipykernel_3540\\2521707949.py:4: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0!\n",
      "You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy.\n",
      "A typical example is when you are setting values in a column of a DataFrame, like:\n",
      "\n",
      "df[\"col\"][row_indexer] = value\n",
      "\n",
      "Use `df.loc[row_indexer, \"col\"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`.\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "  emotional_value['a_type'][emotional_value['amend_weight'] < 0] = 'neg'\n",
      "C:\\Users\\19202\\AppData\\Local\\Temp\\ipykernel_3540\\2521707949.py:4: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  emotional_value['a_type'][emotional_value['amend_weight'] < 0] = 'neg'\n"
     ]
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      ],
      "text/plain": [
       "      content_type  index_content nature word  index_word  amend_weight a_type\n",
       "0              pos              1     ns   东西           0           4.0    pos\n",
       "1              pos              1      v   收到           1           4.0    pos\n",
       "2              pos              1      r  这么久           2           4.0    pos\n",
       "3              pos              1      v    忘           3           4.0    pos\n",
       "4              pos              1      v   好评           4           4.0    pos\n",
       "...            ...            ...    ...  ...         ...           ...    ...\n",
       "14137          neg           1999      q    天           5           1.0    pos\n",
       "14138          neg           1999      v   没人           6           1.0    pos\n",
       "14139          neg           1999      n   售后           7           1.0    pos\n",
       "14140          neg           1999      d    太           8           1.0    pos\n",
       "14141          neg           1999      a    差           9           1.0    pos\n",
       "\n",
       "[14142 rows x 7 columns]"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 给情感值大于0的赋予评论类型'pos'，小于0的赋予'neg'\n",
    "emotional_value['a_type'] = ''\n",
    "emotional_value['a_type'][emotional_value['amend_weight'] > 0] = 'pos'\n",
    "emotional_value['a_type'][emotional_value['amend_weight'] < 0] = 'neg'\n",
    "\n",
    "# 查看情感分析的结果\n",
    "result = pd.merge(left=word, right=emotional_value, on='index_content', how='right')\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "1b23cdf7-cfbf-4f40-ab53-e57a9aad5747",
   "metadata": {},
   "outputs": [
    {
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       "<p>901 rows × 3 columns</p>\n",
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      ],
      "text/plain": [
       "       index_content content_type a_type\n",
       "0                  1          pos    pos\n",
       "14                 2          pos    pos\n",
       "18                 4          pos    pos\n",
       "38                 5          pos    pos\n",
       "61                 6          pos    pos\n",
       "...              ...          ...    ...\n",
       "14095           1988          neg    neg\n",
       "14104           1994          neg    neg\n",
       "14109           1997          neg    neg\n",
       "14129           1998          neg    neg\n",
       "14132           1999          neg    pos\n",
       "\n",
       "[901 rows x 3 columns]"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 去重\n",
    "result = result[['index_content', 'content_type', 'a_type']].drop_duplicates()\n",
    "result"
   ]
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   "cell_type": "code",
   "execution_count": 105,
   "id": "f0dddda7-5e02-4e54-907c-8e0524c020cc",
   "metadata": {},
   "outputs": [
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       "      <th>All</th>\n",
       "      <td>403</td>\n",
       "      <td>498</td>\n",
       "      <td>901</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "a_type        neg  pos  All\n",
       "content_type               \n",
       "neg           363   55  418\n",
       "pos            40  443  483\n",
       "All           403  498  901"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 混淆矩阵-交叉表\n",
    "confusion_matrix = pd.crosstab(result['content_type'], result['a_type'], margins=True)\n",
    "confusion_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "3a113fc1-8944-4ce5-95bf-729de25bb3d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8945615982241953"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 准确率\n",
    "accuracy = (confusion_matrix.iloc[0, 0] + confusion_matrix.iloc[1, 1]) / confusion_matrix.iloc[2, 2]\n",
    "accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "b8c2f1a9-ee8c-419d-bb51-c738118b3833",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.22364039955604884"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 准确率\n",
    "accuracy = (confusion_matrix.iloc[0, 0] + confusion_matrix.iloc[1, 1]) / confusion_matrix.sum().sum()\n",
    "accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "44eaba57-9307-4085-9f2c-0f507f1b6b76",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 提取正负面评论信息\n",
    "# 得到正面评论与负面评论对应的索引\n",
    "ind_pos = list(emotional_value[emotional_value['a_type'] == 'pos']['index_content'])\n",
    "ind_neg = list(emotional_value[emotional_value['a_type'] == 'neg']['index_content'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "f2162ce6-03ff-4571-874b-c8b792c2553f",
   "metadata": {},
   "outputs": [
    {
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      ]
     },
     "execution_count": 109,
     "metadata": {},
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   ],
   "source": [
    "ind_pos"
   ]
  },
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       " 1795,\n",
       " 1797,\n",
       " 1801,\n",
       " 1804,\n",
       " 1805,\n",
       " 1809,\n",
       " 1810,\n",
       " 1811,\n",
       " 1812,\n",
       " 1813,\n",
       " 1814,\n",
       " 1817,\n",
       " 1821,\n",
       " 1823,\n",
       " 1824,\n",
       " 1829,\n",
       " 1831,\n",
       " 1832,\n",
       " 1835,\n",
       " 1837,\n",
       " 1840,\n",
       " 1841,\n",
       " 1842,\n",
       " 1843,\n",
       " 1844,\n",
       " 1846,\n",
       " 1847,\n",
       " 1852,\n",
       " 1853,\n",
       " 1859,\n",
       " 1864,\n",
       " 1868,\n",
       " 1869,\n",
       " 1871,\n",
       " 1872,\n",
       " 1873,\n",
       " 1876,\n",
       " 1878,\n",
       " 1879,\n",
       " 1883,\n",
       " 1887,\n",
       " 1888,\n",
       " 1889,\n",
       " 1893,\n",
       " 1894,\n",
       " 1896,\n",
       " 1899,\n",
       " 1901,\n",
       " 1902,\n",
       " 1904,\n",
       " 1908,\n",
       " 1909,\n",
       " 1910,\n",
       " 1912,\n",
       " 1914,\n",
       " 1915,\n",
       " 1922,\n",
       " 1923,\n",
       " 1924,\n",
       " 1925,\n",
       " 1927,\n",
       " 1928,\n",
       " 1934,\n",
       " 1939,\n",
       " 1941,\n",
       " 1943,\n",
       " 1945,\n",
       " 1947,\n",
       " 1949,\n",
       " 1950,\n",
       " 1951,\n",
       " 1953,\n",
       " 1958,\n",
       " 1959,\n",
       " 1961,\n",
       " 1962,\n",
       " 1963,\n",
       " 1966,\n",
       " 1968,\n",
       " 1969,\n",
       " 1972,\n",
       " 1973,\n",
       " 1975,\n",
       " 1976,\n",
       " 1977,\n",
       " 1978,\n",
       " 1985,\n",
       " 1988,\n",
       " 1994,\n",
       " 1997,\n",
       " 1998]"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ind_neg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "273724dd-c8f1-41b1-a53d-2ec1c99e3dab",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 得到正面评论与负面评论\n",
    "posdata = word[[i in ind_pos for i in word['index_content']]]\n",
    "negdata = word[[i in ind_neg for i in word['index_content']]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "4d7eaa03-fd46-4a55-b03a-cffac9ace3a0",
   "metadata": {},
   "outputs": [
    {
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       "      <td>6</td>\n",
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       "    <tr>\n",
       "      <th>24757</th>\n",
       "      <td>neg</td>\n",
       "      <td>1999</td>\n",
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       "      <td>neg</td>\n",
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       "      <td>9</td>\n",
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       "<p>6673 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      content_type  index_content nature word  index_word\n",
       "0              pos              1     ns   东西           0\n",
       "1              pos              1      v   收到           1\n",
       "2              pos              1      r  这么久           2\n",
       "3              pos              1      v    忘           3\n",
       "4              pos              1      v   好评           4\n",
       "...            ...            ...    ...  ...         ...\n",
       "24755          neg           1999      q    天           5\n",
       "24756          neg           1999      v   没人           6\n",
       "24757          neg           1999      n   售后           7\n",
       "24758          neg           1999      d    太           8\n",
       "24759          neg           1999      a    差           9\n",
       "\n",
       "[6673 rows x 5 columns]"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "posdata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "b7df92e2-64ae-482f-84fa-cae2ae9b1678",
   "metadata": {},
   "outputs": [
    {
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       "      <th>index_word</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>pos</td>\n",
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       "      <td>0</td>\n",
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       "      <th>147</th>\n",
       "      <td>pos</td>\n",
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       "    <tr>\n",
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       "      <td>pos</td>\n",
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       "      <td>neg</td>\n",
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       "      <td>2</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>7469 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      content_type  index_content nature  word  index_word\n",
       "146            pos             11      f     前           0\n",
       "147            pos             11      s    天下           1\n",
       "148            pos             11      v    单买           2\n",
       "149            pos             11      v    用上           3\n",
       "150            pos             11      v    发现           4\n",
       "...            ...            ...    ...   ...         ...\n",
       "24745          neg           1997      f     中          18\n",
       "24746          neg           1997      a    郁闷          19\n",
       "24747          neg           1998      l  好不容易           0\n",
       "24748          neg           1998      n    网购           1\n",
       "24749          neg           1998     nz    漏电           2\n",
       "\n",
       "[7469 rows x 5 columns]"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "negdata"
   ]
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  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "06212b45-da1c-43e4-82f7-1de7d18bab54",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 绘制正面情感词云\n",
    "# 正面情感词词云\n",
    "freq_pos = posdata.groupby(by=['word'])['word'].count()\n",
    "freq_pos = freq_pos.sort_values(ascending=False)\n",
    "backgroud_Image=plt.imread(\"D:/Users/19202/Desktop/pl.jpg\")\n",
    "wordcloud = WordCloud(font_path=\"C:/Windows/Fonts/msyh.ttc\",\n",
    "                      max_words=100,\n",
    "                      background_color='white',\n",
    "                      mask=backgroud_Image)\n",
    "pos_wordcloud = wordcloud.fit_words(freq_pos)\n",
    "\n",
    "plt.imshow(pos_wordcloud)\n",
    "plt.axis('off')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "9470c5e8-4860-4a86-94d8-b4e9cb7a27e2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 绘制负面评论词云\n",
    "freq_neg = negdata.groupby(by=['word'])['word'].count()\n",
    "freq_neg = freq_neg.sort_values(ascending=False)\n",
    "\n",
    "neg_wordcloud = wordcloud.fit_words(freq_neg)\n",
    "\n",
    "plt.imshow(neg_wordcloud)\n",
    "plt.axis('off')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "29167274-4431-41f6-9069-989f881a5876",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "83a0244b-824d-418e-9498-2de2b918d5ed",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "42fff2bd-63ad-4368-bb00-07cf9e4b2c60",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
